FreeCourseSite com Udemy - Machine Learning and Data Science Hands-on with Python and R

1. 1. Machine Learning - Statistics Essentials/1. Machine Learning Introduction.mp420.06MB
2. 1. Machine Learning - Statistics Essentials/10. Technical Terminology.mp454.82MB
3. 1. Machine Learning - Statistics Essentials/11. Error of Observation and Non Observation.mp431.16MB
4. 1. Machine Learning - Statistics Essentials/12. Systematic Sampling.mp454.93MB
5. 1. Machine Learning - Statistics Essentials/13. Cluster Sampling.mp458.79MB
6. 1. Machine Learning - Statistics Essentials/14. Statistics Data Types.mp425.59MB
7. 1. Machine Learning - Statistics Essentials/15. Qualitative Data and Visualization.mp437.69MB
8. 1. Machine Learning - Statistics Essentials/16. Machine Learning.mp456.07MB
9. 1. Machine Learning - Statistics Essentials/17. Relative Frequency Probability.mp462.98MB
10. 1. Machine Learning - Statistics Essentials/18. Joint Probability.mp485.96MB
11. 1. Machine Learning - Statistics Essentials/19. Conditional Probability.mp442.78MB
12. 1. Machine Learning - Statistics Essentials/2. Introduction to Machine Learning with Python.mp46.52MB
13. 1. Machine Learning - Statistics Essentials/20. Concept of Independence.mp440.3MB
14. 1. Machine Learning - Statistics Essentials/21. Total Probability.mp457.65MB
15. 1. Machine Learning - Statistics Essentials/22. Random Variable.mp446.71MB
16. 1. Machine Learning - Statistics Essentials/23. Probability Distribution.mp468.8MB
17. 1. Machine Learning - Statistics Essentials/24. Cumulative Probability Distribution.mp437.58MB
18. 1. Machine Learning - Statistics Essentials/25. Bernoulli Distribution.mp438.71MB
19. 1. Machine Learning - Statistics Essentials/26. Gaussian Distribution.mp433.68MB
20. 1. Machine Learning - Statistics Essentials/27. Geometric Distribution.mp433.2MB
21. 1. Machine Learning - Statistics Essentials/28. Continuous and Normal Distribution.mp449.07MB
22. 1. Machine Learning - Statistics Essentials/29. Mathematical Expression and Computation.mp433.82MB
23. 1. Machine Learning - Statistics Essentials/3. Analytics in Machine Learning.mp447.03MB
24. 1. Machine Learning - Statistics Essentials/30. Transpose of Matrix.mp446.05MB
25. 1. Machine Learning - Statistics Essentials/31. Properties of Matrix.mp447.72MB
26. 1. Machine Learning - Statistics Essentials/32. Determinants.mp447.64MB
27. 1. Machine Learning - Statistics Essentials/33. Error Types.mp453.25MB
28. 1. Machine Learning - Statistics Essentials/34. Critical Value Approach.mp457.08MB
29. 1. Machine Learning - Statistics Essentials/35. Right and Left Sided Critical Approach.mp459.27MB
30. 1. Machine Learning - Statistics Essentials/36. P-Value Approach.mp479.84MB
31. 1. Machine Learning - Statistics Essentials/37. P-Value Approach Continues.mp455.8MB
32. 1. Machine Learning - Statistics Essentials/38. Hypothesis Testing.mp443.49MB
33. 1. Machine Learning - Statistics Essentials/39. Left Tail Test.mp422.9MB
34. 1. Machine Learning - Statistics Essentials/4. Big Data Machine Learning.mp450.99MB
35. 1. Machine Learning - Statistics Essentials/40. Two Tail Test.mp441.64MB
36. 1. Machine Learning - Statistics Essentials/41. Confidence Interval.mp452.67MB
37. 1. Machine Learning - Statistics Essentials/42. Example of Confidence Interval.mp462.96MB
38. 1. Machine Learning - Statistics Essentials/43. Normal and Non Normal Distribution.mp432.45MB
39. 1. Machine Learning - Statistics Essentials/44. Normality Test.mp445.72MB
40. 1. Machine Learning - Statistics Essentials/45. Normality Test Continues.mp440.97MB
41. 1. Machine Learning - Statistics Essentials/46. Determining the Transformation.mp422.14MB
42. 1. Machine Learning - Statistics Essentials/47. T-Test.mp445.2MB
43. 1. Machine Learning - Statistics Essentials/48. T-Test Continue.mp447.22MB
44. 1. Machine Learning - Statistics Essentials/49. More on T-Test.mp455.52MB
45. 1. Machine Learning - Statistics Essentials/5. Emerging Trends Machine Learning.mp472.39MB
46. 1. Machine Learning - Statistics Essentials/50. Test of Independence.mp453.96MB
47. 1. Machine Learning - Statistics Essentials/51. Example of Test of Independence.mp451.13MB
48. 1. Machine Learning - Statistics Essentials/52. Goodness of Fit Test.mp440.22MB
49. 1. Machine Learning - Statistics Essentials/53. Example of Goodness of Fit Test.mp437.93MB
50. 1. Machine Learning - Statistics Essentials/54. Co-Variance.mp417.99MB
51. 1. Machine Learning - Statistics Essentials/55. Co-Variance Continues.mp424.04MB
52. 1. Machine Learning - Statistics Essentials/6. Data Mining.mp443.82MB
53. 1. Machine Learning - Statistics Essentials/7. Data Mining Continues.mp467.73MB
54. 1. Machine Learning - Statistics Essentials/8. Supervised and Unsupervised.mp445.4MB
55. 1. Machine Learning - Statistics Essentials/9. Sampling Method in Machine Learning.mp431.14MB
56. 10. Natural Language Processing (NLP) Tutorials/1. Intoroduction to NLP.mp432.7MB
57. 10. Natural Language Processing (NLP) Tutorials/10. Stemming and Lemmatization Continues.mp461.22MB
58. 10. Natural Language Processing (NLP) Tutorials/11. Convert Token No Stopwords.mp462.67MB
59. 10. Natural Language Processing (NLP) Tutorials/12. Machine Learning Algorithms.mp460.01MB
60. 10. Natural Language Processing (NLP) Tutorials/2. Text Preprocessing.mp439.41MB
61. 10. Natural Language Processing (NLP) Tutorials/3. Feature Extraction.mp44.48MB
62. 10. Natural Language Processing (NLP) Tutorials/4. NLP Installation.mp459.69MB
63. 10. Natural Language Processing (NLP) Tutorials/5. NLP - Demo.mp489.44MB
64. 10. Natural Language Processing (NLP) Tutorials/6. Replacing Contractions.mp4135.03MB
65. 10. Natural Language Processing (NLP) Tutorials/7. Tokenize Dataset.mp469.46MB
66. 10. Natural Language Processing (NLP) Tutorials/8. Remove Stopwords.mp468.24MB
67. 10. Natural Language Processing (NLP) Tutorials/9. Stemming and Lemmatization.mp496.03MB
68. 11. Bayesian Machine Learning AB Testing/1. Introduction to Bayesian Machine Learning.mp436.82MB
69. 11. Bayesian Machine Learning AB Testing/2. Example of Bayesian Machine Learning.mp431.87MB
70. 11. Bayesian Machine Learning AB Testing/3. Example of Bayesian Machine Learning Continues.mp436.13MB
71. 11. Bayesian Machine Learning AB Testing/4. MCMC Module of PYMC Implementation.mp443.41MB
72. 11. Bayesian Machine Learning AB Testing/5. Running the MCMC Module.mp442.54MB
73. 11. Bayesian Machine Learning AB Testing/6. Multiple Variant Testing Using Hierarchial Model.mp445.95MB
74. 11. Bayesian Machine Learning AB Testing/7. Example of Multiple Variant Testing.mp429.38MB
75. 11. Bayesian Machine Learning AB Testing/8. Example of Multiple Variant Testing Continues.mp452.25MB
76. 12. Machine Learning with R/1. Introduction to Machine Learning with Python.mp458.25MB
77. 12. Machine Learning with R/10. 2.10 Problem and Solution.mp479.67MB
78. 12. Machine Learning with R/100. Diagnostic Checking.mp460.55MB
79. 12. Machine Learning with R/101. Forecasting Using Stock Price.mp4108.9MB
80. 12. Machine Learning with R/102. Stock Price Index.mp499.87MB
81. 12. Machine Learning with R/103. Stock Price Index Continues.mp495.16MB
82. 12. Machine Learning with R/104. Prophet Stock.mp450.06MB
83. 12. Machine Learning with R/105. Run Prophet Stock.mp478.21MB
84. 12. Machine Learning with R/106. Time Series Data Denationalization.mp4101.32MB
85. 12. Machine Learning with R/107. Time Series Data Denationalization Continues.mp478.48MB
86. 12. Machine Learning with R/108. Average of Quarter Denationalization.mp4126.96MB
87. 12. Machine Learning with R/109. Regression of Denationalization.mp4103.77MB
88. 12. Machine Learning with R/11. Exponentiation Right to Left.mp453.17MB
89. 12. Machine Learning with R/110. Gradient Boosting Machines.mp467MB
90. 12. Machine Learning with R/111. Errors in Gradient Boosting Machines.mp457.6MB
91. 12. Machine Learning with R/112. What is Error Rate in Gradient Boosting Machines.mp457.55MB
92. 12. Machine Learning with R/113. Optimization Gradient Boosting Machines.mp451.82MB
93. 12. Machine Learning with R/114. Gradient Boosting Trees (GBT).mp438.39MB
94. 12. Machine Learning with R/115. Dataset Boosting in Gradient.mp496.43MB
95. 12. Machine Learning with R/116. Example of Dataset Boosting in Gradient.mp495.79MB
96. 12. Machine Learning with R/117. Example of Dataset Boosting in Gradient Continues.mp4113.25MB
97. 12. Machine Learning with R/118. Market Basket Analysis Association Rules.mp498.38MB
98. 12. Machine Learning with R/119. Market Basket Analysis Association Rules Continues.mp478.3MB
99. 12. Machine Learning with R/12. 2.13 Avoiding Some Common Mistakes.mp469.82MB
100. 12. Machine Learning with R/120. Market Basket Analysis Interpretation.mp450.28MB
101. 12. Machine Learning with R/121. Implementation of Market Basket Analysis.mp430.32MB
102. 12. Machine Learning with R/122. Example of Market Basket Analysis.mp484.78MB
103. 12. Machine Learning with R/123. Datamining in Market Basket Analysis.mp485.97MB
104. 12. Machine Learning with R/124. Market Basket Analysis Using Rstudio.mp478.53MB
105. 12. Machine Learning with R/125. Market Basket Analysis Using Rstudio Continues.mp494.13MB
106. 12. Machine Learning with R/126. More on Rstudio in Market Analysis.mp4122.52MB
107. 12. Machine Learning with R/127. New Development in Machine Learning.mp493.23MB
108. 12. Machine Learning with R/128. Data Scientist in Machine Learnirng.mp474.05MB
109. 12. Machine Learning with R/129. Types of Detection in Machine Learning.mp4102.86MB
110. 12. Machine Learning with R/13. Simple Linear Regression.mp468.16MB
111. 12. Machine Learning with R/130. Example of New Development in Machine Learning.mp479.23MB
112. 12. Machine Learning with R/131. Example of New Development in Machine Learning Continues.mp453.15MB
113. 12. Machine Learning with R/14. Simple Linear Regression Continues.mp439.71MB
114. 12. Machine Learning with R/15. What is Rsquare.mp477.58MB
115. 12. Machine Learning with R/16. Standard Error.mp454.56MB
116. 12. Machine Learning with R/17. General Statistics.mp452.34MB
117. 12. Machine Learning with R/18. General Statistics Continues.mp450.23MB
118. 12. Machine Learning with R/19. Simple Linear Regression and More of Statistics.mp469.26MB
119. 12. Machine Learning with R/2. How do Machine Learn.mp451.66MB
120. 12. Machine Learning with R/20. Open the Studio.mp440.4MB
121. 12. Machine Learning with R/21. What is R Square.mp479.51MB
122. 12. Machine Learning with R/22. What is STD Error.mp455.37MB
123. 12. Machine Learning with R/23. Reject Null Hypothesis.mp484.23MB
124. 12. Machine Learning with R/24. Variance Covariance and Correlation.mp481.89MB
125. 12. Machine Learning with R/25. Root names and Types of Distribution Function.mp471.71MB
126. 12. Machine Learning with R/26. Generating Random Numbers and Combination Function.mp463.1MB
127. 12. Machine Learning with R/27. Probabilities for Discrete Distribution Function.mp483.57MB
128. 12. Machine Learning with R/28. Quantile Function and Poison Distribution.mp477.31MB
129. 12. Machine Learning with R/29. Students T Distribution, Hypothesis and Example.mp463.21MB
130. 12. Machine Learning with R/3. Steps to Apply Machine Learning.mp445.69MB
131. 12. Machine Learning with R/30. Chai-Square Distribution.mp441.33MB
132. 12. Machine Learning with R/31. Data Visualization.mp477.8MB
133. 12. Machine Learning with R/32. More on Data Visualization.mp470.53MB
134. 12. Machine Learning with R/33. Multiple Linear Regression.mp490.37MB
135. 12. Machine Learning with R/34. Multiple Linear Regression Continues.mp469.98MB
136. 12. Machine Learning with R/35. Regression Variables.mp4101.45MB
137. 12. Machine Learning with R/36. Generalized Linear Model.mp493.7MB
138. 12. Machine Learning with R/37. Generalized Least Square.mp488.79MB
139. 12. Machine Learning with R/38. KNN- Various Methods of Distance Measurements.mp452.96MB
140. 12. Machine Learning with R/39. Overview of KNN- (Steps involved).mp471.1MB
141. 12. Machine Learning with R/4. Regression and Classification Problems.mp462.38MB
142. 12. Machine Learning with R/40. Data normalization and prediction on Test Data.mp486.41MB
143. 12. Machine Learning with R/41. Improvement of Model Performance and ROC.mp485.09MB
144. 12. Machine Learning with R/42. Decision Tree Classifier.mp457.8MB
145. 12. Machine Learning with R/43. More on Decision Tree Classifier.mp481.5MB
146. 12. Machine Learning with R/44. Pruning of Decision Trees.mp483.84MB
147. 12. Machine Learning with R/45. Decision Tree Remaining.mp461.11MB
148. 12. Machine Learning with R/46. Decision Tree Remaining Continues.mp446.7MB
149. 12. Machine Learning with R/47. General concept of Random Forest.mp464.3MB
150. 12. Machine Learning with R/48. Ada Boosting and Ensemble Learning.mp495.21MB
151. 12. Machine Learning with R/49. Data Visualization and Preparation.mp489.28MB
152. 12. Machine Learning with R/5. Basic Data Manipulation in R.mp471.68MB
153. 12. Machine Learning with R/50. Tuning Random Forest Model.mp463.4MB
154. 12. Machine Learning with R/51. Evaluation of Random Forest Model Performance.mp465.88MB
155. 12. Machine Learning with R/52. Introduction to Kmeans Clustering.mp475.07MB
156. 12. Machine Learning with R/53. Kmeans Elbow Point and Dataset.mp490.51MB
157. 12. Machine Learning with R/54. Example of Kmeans Dataset.mp4122.65MB
158. 12. Machine Learning with R/55. Creating a Graph for Kmeans Clustering.mp4126.69MB
159. 12. Machine Learning with R/56. Creating a Graph for Kmeans Clustering Continues.mp490.64MB
160. 12. Machine Learning with R/57. Aggregation Function of Clustering.mp478.46MB
161. 12. Machine Learning with R/58. Conditional Probability with Bayes Algorithm.mp482.98MB
162. 12. Machine Learning with R/59. Venn Diagram Naive Bayes Classification.mp461.65MB
163. 12. Machine Learning with R/6. More on Data Manipulation in R.mp462.14MB
164. 12. Machine Learning with R/60. Component OF Bayes Theorem using Frequency Table.mp486.98MB
165. 12. Machine Learning with R/61. Naive Bayes Classification Algorithm and Laplace Estimator.mp470.4MB
166. 12. Machine Learning with R/62. Example of Naive Bayes Classification.mp481.66MB
167. 12. Machine Learning with R/63. Example of Naive Bayes Classification Continues.mp4100.12MB
168. 12. Machine Learning with R/64. Spam and Ham Messages in Word Cloud.mp490.21MB
169. 12. Machine Learning with R/65. Implementation of Dictionary and Document Term Matrix.mp481.48MB
170. 12. Machine Learning with R/66. Executes the Function Naive Bayes.mp489.85MB
171. 12. Machine Learning with R/67. Support Vector Machine with Black Box Method.mp459.63MB
172. 12. Machine Learning with R/68. Linearly and Non- Linearly Support Vector Machine.mp452.99MB
173. 12. Machine Learning with R/69. Kernal Trick.mp457.19MB
174. 12. Machine Learning with R/7. Basic Data Manipulation in R - Practical.mp471.74MB
175. 12. Machine Learning with R/70. Gaussian RBF Kernal and OCR with SVMs.mp481.18MB
176. 12. Machine Learning with R/71. Examples of Gaussian RBF Kernal and OCR with SVMs.mp476.93MB
177. 12. Machine Learning with R/72. Summary of Support Vector Machine.mp478.27MB
178. 12. Machine Learning with R/73. Feature Selection Dimension Reduction Technique.mp486.7MB
179. 12. Machine Learning with R/74. Feature Extraction Dimension Reduction Technique.mp482.53MB
180. 12. Machine Learning with R/75. Dimension Reduction Technique Example.mp488.1MB
181. 12. Machine Learning with R/76. Dimension Reduction Technique Example Continues.mp484.19MB
182. 12. Machine Learning with R/77. Introduction Principal Component Analysis.mp466.74MB
183. 12. Machine Learning with R/78. Steps of PCA.mp461.43MB
184. 12. Machine Learning with R/79. Steps of PCA Continues.mp459.88MB
185. 12. Machine Learning with R/8. Create a Vector.mp463.58MB
186. 12. Machine Learning with R/80. Eigen Values.mp437.75MB
187. 12. Machine Learning with R/81. Eigen Vectors.mp439.57MB
188. 12. Machine Learning with R/82. Principal Component Analysis using Pr-Comp.mp4104.06MB
189. 12. Machine Learning with R/83. Principal Component Analysis using Pr-Comp Continues.mp476.54MB
190. 12. Machine Learning with R/84. C Bind Type in PCA.mp489.65MB
191. 12. Machine Learning with R/85. R Type Model.mp4121.3MB
192. 12. Machine Learning with R/86. Black Box Method in Neural Network.mp487.36MB
193. 12. Machine Learning with R/87. Characteristics of a Neural Networks.mp472.69MB
194. 12. Machine Learning with R/88. Network Topology of a Neural Networks.mp470.49MB
195. 12. Machine Learning with R/89. Weight Adjustment and Case Update.mp480.93MB
196. 12. Machine Learning with R/9. 2.7 Problem and Solution.mp469.89MB
197. 12. Machine Learning with R/90. Introduction Model Building in R.mp4100.93MB
198. 12. Machine Learning with R/91. Installing the Package of Model Building in R.mp488.49MB
199. 12. Machine Learning with R/92. Nodes in Model Building in R.mp470.8MB
200. 12. Machine Learning with R/93. Example of Model Building in R.mp481.6MB
201. 12. Machine Learning with R/94. Time Series Analysis.mp468.49MB
202. 12. Machine Learning with R/95. Pattern in Time Series Data.mp451.02MB
203. 12. Machine Learning with R/96. Time Series Modelling.mp455.94MB
204. 12. Machine Learning with R/97. Moving Average Model.mp467.21MB
205. 12. Machine Learning with R/98. Auto Correlation Function.mp443.08MB
206. 12. Machine Learning with R/99. Inference of ACF and PFCF.mp445.22MB
207. 13. BIP - Business Intelligence Publisher using Siebel/1. Introduction to BIP.mp421MB
208. 13. BIP - Business Intelligence Publisher using Siebel/10. Siebel Applets ‚ Business Obejct and Business Components Part 2.mp490.35MB
209. 13. BIP - Business Intelligence Publisher using Siebel/11. IntegrationObjectsANDIntegrationObjectComponents.mp4101.06MB
210. 13. BIP - Business Intelligence Publisher using Siebel/12. Siebel Views and View Associations to Reports.mp482.77MB
211. 13. BIP - Business Intelligence Publisher using Siebel/13. Siebel HI-OpenUI framworks for BIP Reports and demo of AddIn.mp442.71MB
212. 13. BIP - Business Intelligence Publisher using Siebel/14. Process_Flow_Overview.mp451.8MB
213. 13. BIP - Business Intelligence Publisher using Siebel/15. Process_Flow_ConnectedMode.mp442.29MB
214. 13. BIP - Business Intelligence Publisher using Siebel/16. Process_Flow_DisconnectedMode.mp442.12MB
215. 13. BIP - Business Intelligence Publisher using Siebel/17. Siebel Report Business Service.mp477.34MB
216. 13. BIP - Business Intelligence Publisher using Siebel/2. User Types.mp410.38MB
217. 13. BIP - Business Intelligence Publisher using Siebel/3. Running Modes.mp433.52MB
218. 13. BIP - Business Intelligence Publisher using Siebel/4. Learning about BIP Add-Ins.mp459.81MB
219. 13. BIP - Business Intelligence Publisher using Siebel/5. BIP_Into_5_BIP_AddIn2 and BIP_Into_6.mp464.35MB
220. 13. BIP - Business Intelligence Publisher using Siebel/6. BIP_Into_7_Customized Reports Overview.mp459.34MB
221. 13. BIP - Business Intelligence Publisher using Siebel/7. BIP_Into_8_Developing Reports Overview.mp419.14MB
222. 13. BIP - Business Intelligence Publisher using Siebel/8. Showing Report Views on Application.mp4110.09MB
223. 13. BIP - Business Intelligence Publisher using Siebel/9. Siebel Applets ‚ Business Obejct and Business Components Part 1.mp487.33MB
224. 14. BI - Business Intelligence/1. BI Intro,definition.mp451.19MB
225. 14. BI - Business Intelligence/10. planning deliverables,stage 3.mp434.1MB
226. 14. BI - Business Intelligence/100. Regression Model(Continues).mp444.73MB
227. 14. BI - Business Intelligence/101. Market Basket Analysis Applications.mp446.71MB
228. 14. BI - Business Intelligence/102. Market Basket Analysis Applications(Continues).mp435.93MB
229. 14. BI - Business Intelligence/11. Project Requirement,Data Analysis,Application part 1.mp452.97MB
230. 14. BI - Business Intelligence/12. Project Requirement,Data Analysis,Application part 2.mp465.11MB
231. 14. BI - Business Intelligence/13. Project Requirement,Data Analysis,Application part 3.mp446.98MB
232. 14. BI - Business Intelligence/14. Meta Data.mp411.09MB
233. 14. BI - Business Intelligence/15. data standardisation,meta data,etl,business analysis part 1.mp461.46MB
234. 14. BI - Business Intelligence/16. data standardisation,meta data,etl,business analysis part 2.mp451.14MB
235. 14. BI - Business Intelligence/17. data standardisation,meta data,etl,business analysis part 3.mp420.52MB
236. 14. BI - Business Intelligence/18. ETL Design,Meta DATA ,STAGE 5 CONSTRUCTION DEVELOPMENT RECONCILATION Part 1.mp447.14MB
237. 14. BI - Business Intelligence/19. ETL Design,Meta DATA ,STAGE 5 CONSTRUCTION DEVELOPMENT RECONCILATION Part 2.mp465.35MB
238. 14. BI - Business Intelligence/2. multidimensional db part 1.mp450.11MB
239. 14. BI - Business Intelligence/20. ETL,APPLICATION dEVELOPMENT,DATA gaps,meta data repository,deployment Part 1.mp446.66MB
240. 14. BI - Business Intelligence/21. ETL,APPLICATION dEVELOPMENT,DATA gaps,meta data repository,deployment Part 2.mp417.37MB
241. 14. BI - Business Intelligence/22. ETL,APPLICATION dEVELOPMENT,DATA gaps,meta data repository,deployment Part 3.mp460.84MB
242. 14. BI - Business Intelligence/23. database & recovery,release evaluation.mp430.53MB
243. 14. BI - Business Intelligence/24. post implementation review,toyota case.mp444.88MB
244. 14. BI - Business Intelligence/25. frame work for BI Part 1.mp458.71MB
245. 14. BI - Business Intelligence/26. frame work for BI Part 2.mp456.09MB
246. 14. BI - Business Intelligence/27. frame work for BI Part 3.mp433.11MB
247. 14. BI - Business Intelligence/28. frame work for BI Part 4.mp438.18MB
248. 14. BI - Business Intelligence/29. strategic imperitive of BI Part 1.mp449.28MB
249. 14. BI - Business Intelligence/3. multidimensional db part 2.mp461.19MB
250. 14. BI - Business Intelligence/30. strategic imperitive of BI Part 2.mp441.76MB
251. 14. BI - Business Intelligence/31. Target System.mp447.82MB
252. 14. BI - Business Intelligence/32. Data warehouse and ETL.mp433.03MB
253. 14. BI - Business Intelligence/33. Facebook dataspace management with open source tools.mp438.35MB
254. 14. BI - Business Intelligence/34. Agile Development Process.mp434.55MB
255. 14. BI - Business Intelligence/35. Agile Development Process Continues.mp444.66MB
256. 14. BI - Business Intelligence/36. Challenges on dash board.mp432.28MB
257. 14. BI - Business Intelligence/37. Building Users Expert Profile.mp462.77MB
258. 14. BI - Business Intelligence/38. Semantic Technologies.mp453.11MB
259. 14. BI - Business Intelligence/39. Semantic Tools.mp453.66MB
260. 14. BI - Business Intelligence/4. multidimensional db part 3.mp456.1MB
261. 14. BI - Business Intelligence/40. BI Algorithm By Example.mp442.01MB
262. 14. BI - Business Intelligence/41. Benefits of BI.mp427.67MB
263. 14. BI - Business Intelligence/42. Benefits of BI Continues.mp443.66MB
264. 14. BI - Business Intelligence/43. Amazon.com and Net Flix.mp438.96MB
265. 14. BI - Business Intelligence/44. What is Information Governance.mp449.97MB
266. 14. BI - Business Intelligence/45. Other BI Applications are used to store.mp445.27MB
267. 14. BI - Business Intelligence/46. Designing and Implementing BI Program.mp446.72MB
268. 14. BI - Business Intelligence/47. ETL.mp437.37MB
269. 14. BI - Business Intelligence/48. ETL Continues.mp430.78MB
270. 14. BI - Business Intelligence/49. Loading.mp435.06MB
271. 14. BI - Business Intelligence/5. dbms platform.mp411.8MB
272. 14. BI - Business Intelligence/50. Type 2 Dimension.mp451.92MB
273. 14. BI - Business Intelligence/51. Loading Fact Tables.mp447.39MB
274. 14. BI - Business Intelligence/52. Genearl Idea.mp441.4MB
275. 14. BI - Business Intelligence/53. Conceptual Model.mp436.9MB
276. 14. BI - Business Intelligence/54. Conceptual Model Continues.mp449.97MB
277. 14. BI - Business Intelligence/55. On Going Or Future Works.mp451.43MB
278. 14. BI - Business Intelligence/56. Why Meta Data.mp442.77MB
279. 14. BI - Business Intelligence/57. Essentials Capabilities.mp427.42MB
280. 14. BI - Business Intelligence/58. Common Warehouse Metamodels.mp430.76MB
281. 14. BI - Business Intelligence/59. Data Advantage Group.mp454MB
282. 14. BI - Business Intelligence/6. technical non technical infrastructre part 1.mp443.12MB
283. 14. BI - Business Intelligence/60. DBMS Meta Data Tips.mp464.31MB
284. 14. BI - Business Intelligence/61. For Building The Dataware house(Extraction Team).mp451.68MB
285. 14. BI - Business Intelligence/62. Meta Data Essentials For IT.mp448.65MB
286. 14. BI - Business Intelligence/63. Business Metadata.mp441.09MB
287. 14. BI - Business Intelligence/64. Business Meta Data (Continues).mp424.21MB
288. 14. BI - Business Intelligence/65. Project Planning.mp456.86MB
289. 14. BI - Business Intelligence/66. Project Planning (Continues).mp431.2MB
290. 14. BI - Business Intelligence/67. Deployment Process.mp474.44MB
291. 14. BI - Business Intelligence/68. Chapter Outline.mp439.34MB
292. 14. BI - Business Intelligence/69. Break-Even Analysis.mp437.84MB
293. 14. BI - Business Intelligence/7. technical non technical infrastructre part 2.mp451.18MB
294. 14. BI - Business Intelligence/70. Examples Of Break-Even Analysis.mp443.71MB
295. 14. BI - Business Intelligence/71. Multivirate Analysis.mp449.96MB
296. 14. BI - Business Intelligence/72. Multivirate Analysis (Continues).mp430.93MB
297. 14. BI - Business Intelligence/73. Graphs.mp441.52MB
298. 14. BI - Business Intelligence/74. Why Meta Data Is Important.mp439.52MB
299. 14. BI - Business Intelligence/75. System Development.mp429.91MB
300. 14. BI - Business Intelligence/76. Project Risk Assesment Factors.mp446.31MB
301. 14. BI - Business Intelligence/77. Managing Project Time.mp436.94MB
302. 14. BI - Business Intelligence/78. Prototyping Benefits.mp461.45MB
303. 14. BI - Business Intelligence/79. Incremental Development.mp457.96MB
304. 14. BI - Business Intelligence/8. change control board part 1.mp457.25MB
305. 14. BI - Business Intelligence/80. Incremental Development(Continues).mp447.9MB
306. 14. BI - Business Intelligence/81. What is Cluster Analysis.mp448.92MB
307. 14. BI - Business Intelligence/82. Types Of Clusters.mp449.3MB
308. 14. BI - Business Intelligence/83. Cluster Benefits.mp435.65MB
309. 14. BI - Business Intelligence/84. Kmeans Clustering Method.mp485.92MB
310. 14. BI - Business Intelligence/85. What Is The Problem With PAM.mp461.58MB
311. 14. BI - Business Intelligence/86. BIRCH (1996).mp456.65MB
312. 14. BI - Business Intelligence/87. Density Rechable And Density Conected.mp452.84MB
313. 14. BI - Business Intelligence/88. Denclue Technical Issues.mp465.83MB
314. 14. BI - Business Intelligence/89. The Wave Cluster Algorithm.mp448.29MB
315. 14. BI - Business Intelligence/9. change control board part 2.mp448.58MB
316. 14. BI - Business Intelligence/90. More On Conceptual Clustering.mp460.84MB
317. 14. BI - Business Intelligence/91. Clustering in Quest.mp458.39MB
318. 14. BI - Business Intelligence/92. Why Constraints Based Cluster Analysis.mp451.78MB
319. 14. BI - Business Intelligence/93. What Is Outlier Discovery.mp441.92MB
320. 14. BI - Business Intelligence/94. Segmentation In Data Mining.mp446.47MB
321. 14. BI - Business Intelligence/95. Bottle Neck Of GSP & Spade.mp451.55MB
322. 14. BI - Business Intelligence/96. Why Deal with Sequential Data.mp441.58MB
323. 14. BI - Business Intelligence/97. Algorithm Definition.mp441.85MB
324. 14. BI - Business Intelligence/98. Introduction To Regression Analysis.mp435.34MB
325. 14. BI - Business Intelligence/99. Regression Model.mp453.02MB
326. 2. Machine Learning with Tensorflow for Beginners/1. Introduction to Machine Learning with Tensorflow.mp417.82MB
327. 2. Machine Learning with Tensorflow for Beginners/10. Understanding what Anaconda cloud is.mp480.82MB
328. 2. Machine Learning with Tensorflow for Beginners/100. Run Optimizer.mp413.63MB
329. 2. Machine Learning with Tensorflow for Beginners/101. Create a Range.mp451.4MB
330. 2. Machine Learning with Tensorflow for Beginners/102. Introduction to Neural Networks.mp45.61MB
331. 2. Machine Learning with Tensorflow for Beginners/103. Basic-Concepts.mp4101.53MB
332. 2. Machine Learning with Tensorflow for Beginners/104. Activative Functions.mp499.94MB
333. 2. Machine Learning with Tensorflow for Beginners/105. Activative Functions Input to Output.mp457.72MB
334. 2. Machine Learning with Tensorflow for Beginners/106. Classification Functions.mp461.74MB
335. 2. Machine Learning with Tensorflow for Beginners/107. Tensorflow-Playground.mp4136.67MB
336. 2. Machine Learning with Tensorflow for Beginners/108. Mnist-Dataset.mp454.38MB
337. 2. Machine Learning with Tensorflow for Beginners/109. Mnist-Dataset Continue.mp493.75MB
338. 2. Machine Learning with Tensorflow for Beginners/11. Installation of Anaconda for Windows.mp450.24MB
339. 2. Machine Learning with Tensorflow for Beginners/110. More on Mnist-Dataset.mp481.92MB
340. 2. Machine Learning with Tensorflow for Beginners/12. Installation of Anaconda in Linux.mp429.15MB
341. 2. Machine Learning with Tensorflow for Beginners/13. Using the Jupyter notebook.mp426.08MB
342. 2. Machine Learning with Tensorflow for Beginners/14. Getting started with Anaconda.mp4136.15MB
343. 2. Machine Learning with Tensorflow for Beginners/15. Determining options for Cloudberry.mp439.51MB
344. 2. Machine Learning with Tensorflow for Beginners/16. Introduction to Third Party Libraries.mp48.19MB
345. 2. Machine Learning with Tensorflow for Beginners/18. Numpy-Array Continue.mp484.07MB
346. 2. Machine Learning with Tensorflow for Beginners/19. Arrays.mp4110.36MB
347. 2. Machine Learning with Tensorflow for Beginners/2. Understanding Machine Learning.mp415.54MB
348. 2. Machine Learning with Tensorflow for Beginners/20. Arrays Continue.mp455.4MB
349. 2. Machine Learning with Tensorflow for Beginners/21. Indexing.mp463.28MB
350. 2. Machine Learning with Tensorflow for Beginners/22. Indexing Continue.mp485.08MB
351. 2. Machine Learning with Tensorflow for Beginners/23. Universal Functions.mp4109.59MB
352. 2. Machine Learning with Tensorflow for Beginners/24. Introoduction to Pandas.mp426.06MB
353. 2. Machine Learning with Tensorflow for Beginners/25. Pandas Series.mp433.47MB
354. 2. Machine Learning with Tensorflow for Beginners/26. Pandas Series Continue.mp438.07MB
355. 2. Machine Learning with Tensorflow for Beginners/27. Import Randin.mp464.96MB
356. 2. Machine Learning with Tensorflow for Beginners/28. Import Randin Continue.mp472.37MB
357. 2. Machine Learning with Tensorflow for Beginners/29. Paratmeters.mp487.75MB
358. 2. Machine Learning with Tensorflow for Beginners/3. How do Machines Learns.mp451.9MB
359. 2. Machine Learning with Tensorflow for Beginners/30. Indexing and Database.mp437.9MB
360. 2. Machine Learning with Tensorflow for Beginners/31. Missing Data.mp430.3MB
361. 2. Machine Learning with Tensorflow for Beginners/32. Missing Data-Groupby.mp420.18MB
362. 2. Machine Learning with Tensorflow for Beginners/33. Missing Data-Groupby Continue.mp426.92MB
363. 2. Machine Learning with Tensorflow for Beginners/34. Concat-Merge-Join.mp479.93MB
364. 2. Machine Learning with Tensorflow for Beginners/35. Operations.mp448.08MB
365. 2. Machine Learning with Tensorflow for Beginners/36. Import-Export.mp4104.66MB
366. 2. Machine Learning with Tensorflow for Beginners/37. Python Visualisation.mp449.04MB
367. 2. Machine Learning with Tensorflow for Beginners/38. Mat Plotting.mp463.42MB
368. 2. Machine Learning with Tensorflow for Beginners/39. Multiple Plot Subsections.mp462.39MB
369. 2. Machine Learning with Tensorflow for Beginners/4. Uses of Machine Learning.mp430.21MB
370. 2. Machine Learning with Tensorflow for Beginners/40. API Functionality.mp464.75MB
371. 2. Machine Learning with Tensorflow for Beginners/41. Title of the Plot.mp491.75MB
372. 2. Machine Learning with Tensorflow for Beginners/42. Change Size of Articles.mp459.75MB
373. 2. Machine Learning with Tensorflow for Beginners/43. Two Different Crops.mp454.92MB
374. 2. Machine Learning with Tensorflow for Beginners/44. Mat Plotting Label.mp449.35MB
375. 2. Machine Learning with Tensorflow for Beginners/45. Marker Color.mp472.66MB
376. 2. Machine Learning with Tensorflow for Beginners/46. Create a New Dataframe.mp440.21MB
377. 2. Machine Learning with Tensorflow for Beginners/47. Change the Style.mp444.45MB
378. 2. Machine Learning with Tensorflow for Beginners/48. Index and Value.mp441.35MB
379. 2. Machine Learning with Tensorflow for Beginners/49. Seaborn-Statistical Data Visualization.mp459.06MB
380. 2. Machine Learning with Tensorflow for Beginners/5. Examples with tensorflow by Google.mp457.34MB
381. 2. Machine Learning with Tensorflow for Beginners/50. seaborn library.mp495.97MB
382. 2. Machine Learning with Tensorflow for Beginners/51. Jointplot.mp481.97MB
383. 2. Machine Learning with Tensorflow for Beginners/52. Pairplot.mp4109.81MB
384. 2. Machine Learning with Tensorflow for Beginners/53. Barplot.mp497.54MB
385. 2. Machine Learning with Tensorflow for Beginners/54. Boxplot.mp449.36MB
386. 2. Machine Learning with Tensorflow for Beginners/55. Stripplot.mp478.06MB
387. 2. Machine Learning with Tensorflow for Beginners/56. Matrix.mp492.83MB
388. 2. Machine Learning with Tensorflow for Beginners/57. Matrix Continue.mp433.32MB
389. 2. Machine Learning with Tensorflow for Beginners/58. Grid.mp4110.79MB
390. 2. Machine Learning with Tensorflow for Beginners/59. Grid Continue.mp456.6MB
391. 2. Machine Learning with Tensorflow for Beginners/6. Setting up the Workstation.mp47.06MB
392. 2. Machine Learning with Tensorflow for Beginners/60. Style.mp414.89MB
393. 2. Machine Learning with Tensorflow for Beginners/61. Python Libraries Conclusion.mp413.05MB
394. 2. Machine Learning with Tensorflow for Beginners/62. Introduction To Conda Envirement.mp420.66MB
395. 2. Machine Learning with Tensorflow for Beginners/63. Scikit Learn.mp417.29MB
396. 2. Machine Learning with Tensorflow for Beginners/64. Scikit Learn Continue.mp441.75MB
397. 2. Machine Learning with Tensorflow for Beginners/65. Datasets.mp430.21MB
398. 2. Machine Learning with Tensorflow for Beginners/66. California Dataset.mp460.44MB
399. 2. Machine Learning with Tensorflow for Beginners/67. Data Visualization.mp488.53MB
400. 2. Machine Learning with Tensorflow for Beginners/68. Datavisualization Continue.mp455.48MB
401. 2. Machine Learning with Tensorflow for Beginners/69. Downloading a Test Data.mp490.58MB
402. 2. Machine Learning with Tensorflow for Beginners/7. Understanding program languages.mp46.48MB
403. 2. Machine Learning with Tensorflow for Beginners/70. Population Parameter.mp478.79MB
404. 2. Machine Learning with Tensorflow for Beginners/71. Processing.mp4103.57MB
405. 2. Machine Learning with Tensorflow for Beginners/72. Null Values with Median Value.mp480.14MB
406. 2. Machine Learning with Tensorflow for Beginners/73. Replace Missing Values.mp432.48MB
407. 2. Machine Learning with Tensorflow for Beginners/74. Label Enconder.mp426.02MB
408. 2. Machine Learning with Tensorflow for Beginners/75. Import Labelencoder.mp490.69MB
409. 2. Machine Learning with Tensorflow for Beginners/76. Custom Transformation.mp428.24MB
410. 2. Machine Learning with Tensorflow for Beginners/77. Transformer Custom Transformer.mp456MB
411. 2. Machine Learning with Tensorflow for Beginners/78. Housing with Custom Colums.mp457.03MB
412. 2. Machine Learning with Tensorflow for Beginners/79. Numeric Hosing Data.mp4120.21MB
413. 2. Machine Learning with Tensorflow for Beginners/8. Understanding and Functions of Jupyter.mp465.23MB
414. 2. Machine Learning with Tensorflow for Beginners/80. Liner Regression.mp449.63MB
415. 2. Machine Learning with Tensorflow for Beginners/81. Fine Tuning Model.mp441.43MB
416. 2. Machine Learning with Tensorflow for Beginners/82. Fine Tuning Model Continue.mp457.98MB
417. 2. Machine Learning with Tensorflow for Beginners/83. Quick-Recap.mp45.35MB
418. 2. Machine Learning with Tensorflow for Beginners/84. Tensorflow.mp457.75MB
419. 2. Machine Learning with Tensorflow for Beginners/85. Tensorflow-Hello-World.mp454.6MB
420. 2. Machine Learning with Tensorflow for Beginners/86. Basic Ops.mp478.34MB
421. 2. Machine Learning with Tensorflow for Beginners/87. Basic Ops Continue.mp470.26MB
422. 2. Machine Learning with Tensorflow for Beginners/88. More on Basic Ops.mp467.83MB
423. 2. Machine Learning with Tensorflow for Beginners/89. Eager-Mode.mp448.81MB
424. 2. Machine Learning with Tensorflow for Beginners/9. Learning of Jupyter installation.mp45.03MB
425. 2. Machine Learning with Tensorflow for Beginners/90. Concept.mp437.51MB
426. 2. Machine Learning with Tensorflow for Beginners/91. Linear-Regression.mp425.28MB
427. 2. Machine Learning with Tensorflow for Beginners/92. Linear-Model.mp445.39MB
428. 2. Machine Learning with Tensorflow for Beginners/93. Matrix Multiplication Function.mp475.5MB
429. 2. Machine Learning with Tensorflow for Beginners/94. Practice for a Simple Linear Model.mp424.42MB
430. 2. Machine Learning with Tensorflow for Beginners/95. Cost Function.mp423MB
431. 2. Machine Learning with Tensorflow for Beginners/96. Creative Optimizer.mp436.16MB
432. 2. Machine Learning with Tensorflow for Beginners/97. RR Input and Output Value.mp427.46MB
433. 2. Machine Learning with Tensorflow for Beginners/98. Logistic-Regression.mp451.55MB
434. 2. Machine Learning with Tensorflow for Beginners/99. Global Variabales Initializer.mp436.5MB
435. 3. Machine Learning Project #1 - Shipping and Time Estimation/1. Introduction to Shipping and pricing.mp425.71MB
436. 3. Machine Learning Project #1 - Shipping and Time Estimation/10. Demand Forecasting.mp485.19MB
437. 3. Machine Learning Project #1 - Shipping and Time Estimation/11. Distribution of Attributes.mp463.71MB
438. 3. Machine Learning Project #1 - Shipping and Time Estimation/12. Spending Distribution.mp482.72MB
439. 3. Machine Learning Project #1 - Shipping and Time Estimation/13. Normalization and Discretization.mp4119.5MB
440. 3. Machine Learning Project #1 - Shipping and Time Estimation/2. Inventory Status.mp4104.65MB
441. 3. Machine Learning Project #1 - Shipping and Time Estimation/3. Defining Data Type.mp495.45MB
442. 3. Machine Learning Project #1 - Shipping and Time Estimation/4. Data for Validation.mp4103.3MB
443. 3. Machine Learning Project #1 - Shipping and Time Estimation/5. Finding the Corelation.mp472.68MB
444. 3. Machine Learning Project #1 - Shipping and Time Estimation/6. Density for Numeric Attribute.mp487.96MB
445. 3. Machine Learning Project #1 - Shipping and Time Estimation/7. Method for Train Control.mp450.5MB
446. 3. Machine Learning Project #1 - Shipping and Time Estimation/8. Assigning a Training Set.mp4125.2MB
447. 3. Machine Learning Project #1 - Shipping and Time Estimation/9. Mean Absolute Error.mp471.41MB
448. 4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/1. Introduction to Supply Chain.mp4100.34MB
449. 4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/2. G Plot of Heatmap.mp478.74MB
450. 4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/3. Checking the Function Argument.mp4121.19MB
451. 4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/4. Heatmap for Discretized Dataset.mp488.57MB
452. 4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/5. Distinguished Methods with Single.mp443.58MB
453. 4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/6. Analyzing both the Plots.mp472.83MB
454. 4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/7. Defining the Lengths.mp4101.48MB
455. 4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/8. Using Different Clusters.mp454.16MB
456. 5. Machine Learning Project #3 - Predicting Prices using Regression/1. Introduction to Predicting Prices Using Regression.mp458.91MB
457. 5. Machine Learning Project #3 - Predicting Prices using Regression/10. Replacing Features with Values.mp483.71MB
458. 5. Machine Learning Project #3 - Predicting Prices using Regression/11. Assigning Quantatative Variables.mp445.85MB
459. 5. Machine Learning Project #3 - Predicting Prices using Regression/12. Converting Columns to Cordinal Forms.mp448.87MB
460. 5. Machine Learning Project #3 - Predicting Prices using Regression/13. Evaluating the Garage Finish Colummn.mp466.18MB
461. 5. Machine Learning Project #3 - Predicting Prices using Regression/14. Checking Shape of Data Frame.mp414.86MB
462. 5. Machine Learning Project #3 - Predicting Prices using Regression/15. Spliting Data to Train and Test.mp468.83MB
463. 5. Machine Learning Project #3 - Predicting Prices using Regression/16. Algorithm for Predicting Test Values.mp428MB
464. 5. Machine Learning Project #3 - Predicting Prices using Regression/2. Proximity to Various Conditions.mp464.34MB
465. 5. Machine Learning Project #3 - Predicting Prices using Regression/3. Number of Fire Places.mp430.23MB
466. 5. Machine Learning Project #3 - Predicting Prices using Regression/4. Adding the Test Value.mp482.62MB
467. 5. Machine Learning Project #3 - Predicting Prices using Regression/5. Index to the ID Column.mp468.2MB
468. 5. Machine Learning Project #3 - Predicting Prices using Regression/6. Model on Data Set.mp482.18MB
469. 5. Machine Learning Project #3 - Predicting Prices using Regression/7. Missing Value Imputation.mp456.37MB
470. 5. Machine Learning Project #3 - Predicting Prices using Regression/8. Substituting Features with Value.mp491.78MB
471. 5. Machine Learning Project #3 - Predicting Prices using Regression/9. Imputing a Row using at Command.mp471.67MB
472. 6. Machine Learning Project #4 - Banking and Credit Frauds/1. Introduction to Banking System.mp417.11MB
473. 6. Machine Learning Project #4 - Banking and Credit Frauds/2. Laon Status Grade.mp493.48MB
474. 6. Machine Learning Project #4 - Banking and Credit Frauds/3. Logistic Regression and Logistic Question.mp464.52MB
475. 6. Machine Learning Project #4 - Banking and Credit Frauds/4. Beta Value.mp448.28MB
476. 6. Machine Learning Project #4 - Banking and Credit Frauds/5. Predict Value.mp477.82MB
477. 6. Machine Learning Project #4 - Banking and Credit Frauds/6. Performance Value.mp463.65MB
478. 6. Machine Learning Project #4 - Banking and Credit Frauds/7. Fals Positive Rate.mp443.37MB
479. 7. Machine Learning Project #5 - Fraud Detection in Credit Payments/1. Introduction to Fraud Detection in Credit Payments.mp417.35MB
480. 7. Machine Learning Project #5 - Fraud Detection in Credit Payments/10. VRS.mp4107.46MB
481. 7. Machine Learning Project #5 - Fraud Detection in Credit Payments/11. CRS Efficiency and Efficiency.mp453.09MB
482. 7. Machine Learning Project #5 - Fraud Detection in Credit Payments/2. Installation of Packages.mp472.81MB
483. 7. Machine Learning Project #5 - Fraud Detection in Credit Payments/3. Risk Analytics.mp482.51MB
484. 7. Machine Learning Project #5 - Fraud Detection in Credit Payments/4. Trading Companies and Stocks.mp497.65MB
485. 7. Machine Learning Project #5 - Fraud Detection in Credit Payments/5. DEA with Input or Profit and Loss.mp487.78MB
486. 7. Machine Learning Project #5 - Fraud Detection in Credit Payments/6. Efficiency Profit and Loss.mp464.71MB
487. 7. Machine Learning Project #5 - Fraud Detection in Credit Payments/7. Rank Functions.mp476.44MB
488. 7. Machine Learning Project #5 - Fraud Detection in Credit Payments/8. RHS Constaints.mp489.36MB
489. 7. Machine Learning Project #5 - Fraud Detection in Credit Payments/9. Profit and Loss Report.mp473.11MB
490. 8. AWS Machine Learning/1. Introduction to Amazon Machine Learning (AML).mp438.18MB
491. 8. AWS Machine Learning/10. Example of Data Insight In AML.mp466.85MB
492. 8. AWS Machine Learning/11. More on Data Insight In AML.mp454.57MB
493. 8. AWS Machine Learning/12. ML Model Example in Data Sources.mp490.66MB
494. 8. AWS Machine Learning/13. Creating ML Model Evaluating.mp484.6MB
495. 8. AWS Machine Learning/14. Advanced Setting In ML Model.mp438.46MB
496. 8. AWS Machine Learning/15. Creating ML Model for Batch Prediction.mp484.89MB
497. 8. AWS Machine Learning/16. Batch Prediction Result.mp447.61MB
498. 8. AWS Machine Learning/17. Overvies of ML Model Handson.mp465.33MB
499. 8. AWS Machine Learning/18. ML objects Handson in ML.mp445.63MB
500. 8. AWS Machine Learning/2. Lifecycle of AML.mp443.45MB
501. 8. AWS Machine Learning/3. Connecting to Data Source in AML.mp418.8MB
502. 8. AWS Machine Learning/4. Creating Data Scheme in AML.mp426.88MB
503. 8. AWS Machine Learning/5. Invaild Value and Varible Target in AML.mp44.41MB
504. 8. AWS Machine Learning/6. ML Models in AML.mp458.71MB
505. 8. AWS Machine Learning/7. Manging ML Object in AML.mp412.02MB
506. 8. AWS Machine Learning/8. Creating DataSource Handson.mp4104.1MB
507. 8. AWS Machine Learning/9. Creating DataSource Handson Continues.mp469.95MB
508. 9. Deep Learning Tutorials/1. Introduction to Deep Learning.mp428.08MB
509. 9. Deep Learning Tutorials/10. Data for Classifier.mp449.77MB
510. 9. Deep Learning Tutorials/11. Implementing with Keras.mp445.54MB
511. 9. Deep Learning Tutorials/12. Values in Data Set.mp472.42MB
512. 9. Deep Learning Tutorials/13. Components in Data Set.mp479.14MB
513. 9. Deep Learning Tutorials/14. Models in Data Set.mp462.07MB
514. 9. Deep Learning Tutorials/2. Structure of Neural Network.mp435.22MB
515. 9. Deep Learning Tutorials/3. Moving Through Neural Network.mp438.04MB
516. 9. Deep Learning Tutorials/4. Types of Activation Functions.mp420.42MB
517. 9. Deep Learning Tutorials/5. Optimizing Back Propagation.mp444.98MB
518. 9. Deep Learning Tutorials/6. Briefing on Tensor Flow.mp435.78MB
519. 9. Deep Learning Tutorials/7. Installation of Tensor Flow.mp423.24MB
520. 9. Deep Learning Tutorials/8. Implementatiion on Neural Package.mp481.87MB
521. 9. Deep Learning Tutorials/9. Implementatiion on Neural Package Continues.mp469.05MB