Computer Vision Projects with Python 3 Video

1. 4.Deep Learning Image Classification with TensorFlow/17.Retraining with Our Own Images.mp452MB
2. 1.Introduction and Tool Setup/02.Downloading and Installing Python 3_Anaconda.mp422.1MB
3. 1.Introduction and Tool Setup/03.Installing Additional Libraries.mp447.15MB
4. 1.Introduction and Tool Setup/04.Exploring the Jupyter Notebook.mp434.74MB
5. 2.Handwritten Digit Recognition with scikit-learn and TensorFlow/05.Acquiring and Processing MNIST Digit Data.mp424.63MB
6. 2.Handwritten Digit Recognition with scikit-learn and TensorFlow/06.Creating and Training a Support Vector Machine.mp47.86MB
7. 2.Handwritten Digit Recognition with scikit-learn and TensorFlow/07.Applying the Support Vector Machine to New Data.mp431.49MB
8. 2.Handwritten Digit Recognition with scikit-learn and TensorFlow/08.Introducing TensorFlow with Digit Classification.mp439.09MB
9. 2.Handwritten Digit Recognition with scikit-learn and TensorFlow/09.Evaluating the Results.mp412.74MB
10. 3.Facial Feature Tracking and Classification with dlib/10.Introducing dlib.mp426.93MB
11. 3.Facial Feature Tracking and Classification with dlib/11.What Are Facial Landmarks.mp412.78MB
12. 3.Facial Feature Tracking and Classification with dlib/12.Example One – Finding 68 Facial Landmarks in Images.mp440.09MB
13. 3.Facial Feature Tracking and Classification with dlib/13.Example Two – Faces in Videos.mp419.03MB
14. 3.Facial Feature Tracking and Classification with dlib/14.Example Three – Facial Recognition.mp437.58MB
15. 4.Deep Learning Image Classification with TensorFlow/15.A Deeper Introduction to TensorFlow.mp422.18MB
16. 4.Deep Learning Image Classification with TensorFlow/16.Using a Pre-Trained Model (Inception) for Image Classification.mp444.54MB
17. 1.Introduction and Tool Setup/01.The Course Overview.mp413.39MB
18. 4.Deep Learning Image Classification with TensorFlow/18.Speeding Up Computations with GPUs.mp417.53MB