41. Project-40 Build Similarity In-Text Django App -Deploy On Heroku/2. Cleaning the data.mp490.92MB
41. Project-40 Build Similarity In-Text Django App -Deploy On Heroku/3. Building the model.mp4130.68MB
41. Project-40 Build Similarity In-Text Django App -Deploy On Heroku/4. Implementing Django web application.mp4105.28MB
41. Project-40 Build Similarity In-Text Django App -Deploy On Heroku/5. Deploying On Heroku.mp455.21MB
42. Project-41 Heart Attack Risk Prediction Using Eval ML (Auto ML)/1. Introduction to the Project.mp423.76MB
42. Project-41 Heart Attack Risk Prediction Using Eval ML (Auto ML)/2. Importing Libraries and Datasets.mp415.69MB
42. Project-41 Heart Attack Risk Prediction Using Eval ML (Auto ML)/3. Data Analysis.mp456.06MB
42. Project-41 Heart Attack Risk Prediction Using Eval ML (Auto ML)/4. Model Building Part.mp446.71MB
42. Project-41 Heart Attack Risk Prediction Using Eval ML (Auto ML)/5. Model Building Part 2.mp433.63MB
42. Project-41 Heart Attack Risk Prediction Using Eval ML (Auto ML)/6. Model building and Predictions using Auto ML(Eval ML).mp461.4MB
43. Project-42 Credit Card Fraud Detection Using Pycaret (Auto ML)/1. Introduction to the Project.mp429.56MB
43. Project-42 Credit Card Fraud Detection Using Pycaret (Auto ML)/2. Importing Libraries and DataSet.mp427.4MB
43. Project-42 Credit Card Fraud Detection Using Pycaret (Auto ML)/3. Data Analysis.mp443.33MB
43. Project-42 Credit Card Fraud Detection Using Pycaret (Auto ML)/4. Model Building using ML.mp458.32MB
43. Project-42 Credit Card Fraud Detection Using Pycaret (Auto ML)/5. Model Building and Prediction using PyCaret (AutoML).mp497.03MB
44. Project-43 Flight Fare Prediction Using Auto SK Learn (Auto ML)/1. Introduction to the Project.mp421.9MB
44. Project-43 Flight Fare Prediction Using Auto SK Learn (Auto ML)/2. Importing Libraries and DataSet.mp445.2MB
44. Project-43 Flight Fare Prediction Using Auto SK Learn (Auto ML)/3. Data Analysis.mp431.66MB
44. Project-43 Flight Fare Prediction Using Auto SK Learn (Auto ML)/4. Feature Engineering 1.mp443.61MB
44. Project-43 Flight Fare Prediction Using Auto SK Learn (Auto ML)/5. Feature Engineering 2.mp450.68MB
44. Project-43 Flight Fare Prediction Using Auto SK Learn (Auto ML)/6. Feature Selection.mp425.02MB
44. Project-43 Flight Fare Prediction Using Auto SK Learn (Auto ML)/7. Model Building using ML.mp438.48MB
44. Project-43 Flight Fare Prediction Using Auto SK Learn (Auto ML)/8. Model Building and Prediction using Auto SK Learn.mp441.89MB
45. Project-44 Petrol Price Forecasting Using Auto Keras/1. Introduction to the Project.mp430.61MB
45. Project-44 Petrol Price Forecasting Using Auto Keras/2. Importing Libraries and Data Set.mp420.01MB
45. Project-44 Petrol Price Forecasting Using Auto Keras/3. Data Analysis and splitting of Data.mp439.97MB
45. Project-44 Petrol Price Forecasting Using Auto Keras/4. Data Preprocessing.mp436.82MB
45. Project-44 Petrol Price Forecasting Using Auto Keras/5. Model Building and Prediction using LSTM model.mp432.58MB
45. Project-44 Petrol Price Forecasting Using Auto Keras/6. Model Building and prediction using ARIMA and Auto Keras (Auto ML).mp437.51MB
46. Project-45 Bank Customer Churn Prediction Using H2O Auto ML/1. Introduction to the Project.mp433.05MB
46. Project-45 Bank Customer Churn Prediction Using H2O Auto ML/2. Importing Libraries and DataSet.mp425.04MB
46. Project-45 Bank Customer Churn Prediction Using H2O Auto ML/3. Data Analysis.mp465.22MB
46. Project-45 Bank Customer Churn Prediction Using H2O Auto ML/4. Feature Engineering.mp447.36MB
46. Project-45 Bank Customer Churn Prediction Using H2O Auto ML/5. Model Building and Prediction using ANN.mp434.15MB
46. Project-45 Bank Customer Churn Prediction Using H2O Auto ML/6. Model Building and Prediction using H2O Auto ML(Auto ML).mp491.9MB
47. Project-46 Air Quality Index Predictor Using TPOT With Deployment (Auto ML)/1. Introduction to the Project.mp435.39MB
47. Project-46 Air Quality Index Predictor Using TPOT With Deployment (Auto ML)/2. Importing Libraries and Data sets.mp431.01MB
47. Project-46 Air Quality Index Predictor Using TPOT With Deployment (Auto ML)/3. Data Analysis.mp467.73MB
47. Project-46 Air Quality Index Predictor Using TPOT With Deployment (Auto ML)/4. Feature Engineering.mp430.66MB
47. Project-46 Air Quality Index Predictor Using TPOT With Deployment (Auto ML)/5. Model Building using ML- 1.mp469.08MB
47. Project-46 Air Quality Index Predictor Using TPOT With Deployment (Auto ML)/6. Model Building using ML- 2.mp445.06MB
47. Project-46 Air Quality Index Predictor Using TPOT With Deployment (Auto ML)/7. Model Building and Predictions using TPOT Library (Auto ML).mp443.4MB
47. Project-46 Air Quality Index Predictor Using TPOT With Deployment (Auto ML)/8. Deployment of Model using Flask API.mp463.35MB
48. Project-47 Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)/1. Introduction to the Project.mp421.45MB
48. Project-47 Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)/2. Importing Libraries and DataSet.mp445.63MB
48. Project-47 Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)/3. Data Analysis and Handling Missing Values- 1.mp438.33MB
48. Project-47 Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)/4. Data Analysis and Handling Missing Values- 2.mp450.05MB
48. Project-47 Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)/5. Feature Engineering.mp470.43MB
48. Project-47 Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)/6. Model Building using ML Algorithms.mp452.84MB
48. Project-47 Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)/7. Model Building and Prediction using PyCaret (AutoML).mp468.96MB
48. Project-47 Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)/8. Using FLASK API.mp450.77MB
48. Project-47 Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)/9. Deploying model using Heroku.mp433.27MB
49. Project-48 Pizza Price Prediction Using ML And EVALML(Auto ML)/1. Introduction to the project.mp426.01MB
49. Project-48 Pizza Price Prediction Using ML And EVALML(Auto ML)/2. Importing Libraries and DataSet.mp435.07MB
49. Project-48 Pizza Price Prediction Using ML And EVALML(Auto ML)/3. Data Analysis.mp467.34MB
49. Project-48 Pizza Price Prediction Using ML And EVALML(Auto ML)/4. Feature Engineering.mp453.75MB
49. Project-48 Pizza Price Prediction Using ML And EVALML(Auto ML)/5. Model Building using ML models.mp443.41MB
49. Project-48 Pizza Price Prediction Using ML And EVALML(Auto ML)/6. Model Building and Prediction using EVAL ML(Auto ML).mp497.74MB
5. Project-4 Traffic sign classification/1. Introduction to traffic sign classification.mp430.82MB
5. Project-4 Traffic sign classification/2. importing the data and libraries.mp457.48MB