[FreeCourseSite.com] Udemy - Tensorflow 2.0 Deep Learning and Artificial Intelligence

•  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