| 18. Setting up your Environment (FAQ by Student Request)/2. Anaconda Environment Setup.mp4 | 180.9 MB |
| 18. Setting up your Environment (FAQ by Student Request)/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4 | 167.3 MB |
| 18. Setting up your Environment (FAQ by Student Request)/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 | 150.59 MB |
| 6. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem.mp4 | 124.05 MB |
| 20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 | 108.17 MB |
| 20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 | 105.61 MB |
| 13. Advanced Tensorflow Usage/2. Tensorflow Serving pt 2.mp4 | 104.99 MB |
| 11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.mp4 | 98.59 MB |
| 6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4 | 90.15 MB |
| 10. GANs (Generative Adversarial Networks)/1. GAN Theory.mp4 | 87.16 MB |
| 6. Recurrent Neural Networks, Time Series, and Sequence Data/5. Recurrent Neural Networks.mp4 | 83 MB |
| 5. Convolutional Neural Networks/5. CNN Architecture.mp4 | 80.58 MB |
| 4. Feedforward Artificial Neural Networks/5. Activation Functions.mp4 | 80.54 MB |
| 6. Recurrent Neural Networks, Time Series, and Sequence Data/9. GRU and LSTM (pt 1).mp4 | 79.86 MB |
| 5. Convolutional Neural Networks/1. What is Convolution (part 1).mp4 | 79.77 MB |
| 20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 | 79.71 MB |
| 10. GANs (Generative Adversarial Networks)/2. GAN Code.mp4 | 78.3 MB |
| 5. Convolutional Neural Networks/6. CNN Code Preparation.mp4 | 76.88 MB |
| 19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. Beginner's Coding Tips.mp4 | 75.71 MB |
| 6. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4 | 74.07 MB |
| 1. Welcome/2. Outline.mp4 | 73.67 MB |
| 2. Google Colab/3. Uploading your own data to Google Colab.mp4 | 73.59 MB |
| 5. Convolutional Neural Networks/11. Improving CIFAR-10 Results.mp4 | 72.91 MB |
| 19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code Yourself (part 1).mp4 | 71.85 MB |
| 6. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction.mp4 | 71.7 MB |
| 4. Feedforward Artificial Neural Networks/7. How to Represent Images.mp4 | 70.46 MB |
| 19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Proof that using Jupyter Notebook is the same as not using it.mp4 | 69.45 MB |
| 5. Convolutional Neural Networks/4. Convolution on Color Images.mp4 | 69.44 MB |
| 4. Feedforward Artificial Neural Networks/10. ANN for Regression.mp4 | 69.27 MB |
| 8. Recommender Systems/1. Recommender Systems with Deep Learning Theory.mp4 | 68.66 MB |
| 4. Feedforward Artificial Neural Networks/2. Beginners Rejoice The Math in This Course is Optional.mp4 | 68.52 MB |
| 12. Stock Trading Project with Deep Reinforcement Learning/6. Code pt 2.mp4 | 68 MB |
| 6. Recurrent Neural Networks, Time Series, and Sequence Data/17. Stock Return Predictions using LSTMs (pt 3).mp4 | 67.34 MB |
| 6. Recurrent Neural Networks, Time Series, and Sequence Data/15. Stock Return Predictions using LSTMs (pt 1).mp4 | 67.11 MB |
| 9. Transfer Learning for Computer Vision/5. Transfer Learning Code (pt 1).mp4 | 66.52 MB |
| 3. Machine Learning and Neurons/1. What is Machine Learning.mp4 | 65.5 MB |
| 6. Recurrent Neural Networks, Time Series, and Sequence Data/11. A More Challenging Sequence.mp4 | 64.65 MB |
| 1. Welcome/3. Where to get the code.mp4 | 62.91 MB |
| 11. Deep Reinforcement Learning (Theory)/11. Q-Learning.mp4 | 61.83 MB |
| 3. Machine Learning and Neurons/2. Code Preparation (Classification Theory).mp4 | 59.8 MB |
| 8. Recommender Systems/2. Recommender Systems with Deep Learning Code.mp4 | 58.81 MB |
| 14. Low-Level Tensorflow/4. Build Your Own Custom Model.mp4 | 58.55 MB |
| 3. Machine Learning and Neurons/5. Regression Notebook.mp4 | 57.47 MB |
| 7. Natural Language Processing (NLP)/2. Code Preparation (NLP).mp4 | 57.04 MB |
| 4. Feedforward Artificial Neural Networks/4. The Geometrical Picture.mp4 | 56.43 MB |
| 11. Deep Reinforcement Learning (Theory)/12. Deep Q-Learning DQN (pt 1).mp4 | 56.27 MB |
| 14. Low-Level Tensorflow/3. Variables and Gradient Tape.mp4 | 56.05 MB |
| 9. Transfer Learning for Computer Vision/1. Transfer Learning Theory.mp4 | 55.13 MB |
| 16. In-Depth Gradient Descent/5. Adam (pt 1).mp4 | 55.12 MB |
| 3. Machine Learning and Neurons/3. Classification Notebook.mp4 | 54.54 MB |