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    [Tutorialsplanet.NET] Udemy - PyTorch Deep Learning and Artificial Intelligence
- Date: 2024-10-01
 - Size: 1.3 GB
 - Files: 45
 
File Name
                Size
            1. Introduction/1. Welcome.mp4.!qB
                36 MB
            1. Introduction/1. Welcome.vtt
                5.0 kB
            1. Introduction/2. Overview and Outline.mp4.!qB
                4.3 MB
            11. Deep Reinforcement Learning (Theory)/11. Q-Learning.mp4.!qB
                16 MB
            11. Deep Reinforcement Learning (Theory)/13. Deep Q-Learning  DQN (pt 2).mp4.!qB
                52 MB
            11. Deep Reinforcement Learning (Theory)/13. Deep Q-Learning  DQN (pt 2).vtt
                12 kB
            11. Deep Reinforcement Learning (Theory)/14. How to Learn Reinforcement Learning.mp4.!qB
                4.8 MB
            11. Deep Reinforcement Learning (Theory)/2. Elements of a Reinforcement Learning Problem.mp4.!qB
                85 MB
            11. Deep Reinforcement Learning (Theory)/5. The Return.mp4.!qB
                13 MB
            12. Stock Trading Project with Deep Reinforcement Learning/2. Data and Environment.mp4.!qB
                53 MB
            12. Stock Trading Project with Deep Reinforcement Learning/7. Code pt 3.mp4.!qB
                18 MB
            13. VIP Uncertainty Estimation/1. Custom Loss and Estimating Prediction Uncertainty.mp4.!qB
                44 MB
            13. VIP Uncertainty Estimation/1. Custom Loss and Estimating Prediction Uncertainty.vtt
                11 kB
            13. VIP Uncertainty Estimation/2. Estimating Prediction Uncertainty Code.mp4.!qB
                5.5 MB
            16. In-Depth Gradient Descent/5. Adam (pt 1).mp4.!qB
                55 MB
            16. In-Depth Gradient Descent/5. Adam (pt 1).vtt
                15 kB
            16. In-Depth Gradient Descent/6. Adam (pt 2).mp4.!qB
                1.6 MB
            18. Setting up your Environment (FAQ by Student Request)/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4.!qB
                151 MB
            18. Setting up your Environment (FAQ by Student Request)/1. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt
                13 kB
            18. Setting up your Environment (FAQ by Student Request)/2. Windows-Focused Environment Setup 2018.mp4.!qB
                6.1 MB
            18. Setting up your Environment (FAQ by Student Request)/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4.!qB
                167 MB
            18. Setting up your Environment (FAQ by Student Request)/3. Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.vtt
                28 kB
            19. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code Yourself (part 1).mp4.!qB
                2.1 MB
            2. Google Colab/1. Intro to Google Colab, how to use a GPU or TPU for free.mp4.!qB
                60 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
                0 B
            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.vtt
                0 B
            20. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4.!qB
                29 MB
            3. Machine Learning and Neurons/16. Train Sets vs. Validation Sets vs. Test Sets.mp4.!qB
                42 MB
            3. Machine Learning and Neurons/6. Moore's Law Notebook.mp4.!qB
                65 MB
            5. Convolutional Neural Networks/13. Improving CIFAR-10 Results.mp4.!qB
                21 MB
            5. Convolutional Neural Networks/5. CNN Architecture.mp4.!qB
                70 MB
            5. Convolutional Neural Networks/6. CNN Code Preparation (part 1).mp4.!qB
                28 MB
            5. Convolutional Neural Networks/9. CNN for Fashion MNIST.mp4.!qB
                41 MB
            6. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4.!qB
                38 MB
            6. Recurrent Neural Networks, Time Series, and Sequence Data/10. GRU and LSTM (pt 2).mp4.!qB
                20 MB
            6. Recurrent Neural Networks, Time Series, and Sequence Data/15. Stock Return Predictions using LSTMs (pt 2).mp4.!qB
                32 MB
            6. Recurrent Neural Networks, Time Series, and Sequence Data/17. Other Ways to Forecast.mp4.!qB
                14 MB
            6. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4.!qB
                33 MB
            7. Natural Language Processing (NLP)/6. Text Classification with LSTMs.mp4.!qB
                31 MB
            7. Natural Language Processing (NLP)/9. VIP Making Predictions with a Trained NLP Model.mp4.!qB
                49 MB
            7. Natural Language Processing (NLP)/9. VIP Making Predictions with a Trained NLP Model.vtt
                8.0 kB
            7. Natural Language Processing (NLP)/[Tutorialsplanet.NET].url
                128 B
            8. Recommender Systems/1. Recommender Systems with Deep Learning Theory.mp4.!qB
                3.6 MB
            8. Recommender Systems/2. Recommender Systems with Deep Learning Code Preparation.mp4.!qB
                19 MB
            8. Recommender Systems/4. Recommender Systems with Deep Learning Code (pt 2).mp4.!qB
                69 MB