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Udemy Reinforcement Learning for Algorithmic Trading with Python - AD-TEAM - 10-01-2024 5.03 GB | 00:11:57 | mp4 | 1280X720 | 16:9 Genre:eLearning |Language:English
Files Included :
1 - Welcome and Introduction (22.18 MB) 2 - How to get the most out of this course (39.14 MB) 3 - Course Materials Downloads (27.04 MB) 1 - Download and Install Anaconda (63.81 MB) 2 - How to open Jupyter Notebooks (84.37 MB) 3 - How to work with Jupyter Notebooks (81.15 MB) 1 - Introduction (12.52 MB) 2 - Loading and inspecting the Dataset with Pandas (67.21 MB) 3 - Prices and Financial Returns (40.28 MB) 4 - Simple Moving Averages (SMA) (41.4 MB) 5 - Excursus Creating Technical Indicators with Pandas (24.55 MB) 6 - MACD Lines (22.7 MB) 7 - Relative Strength Index (RSI) (18.28 MB) 8 - Stochastic Oscillators & Conclusion (103.33 MB) 1 - What is ChatGPT and how does it work (17.22 MB) 10 - Prompt Engineering Techniques (Part 2) (51.34 MB) 11 - Prompt Engineering Techniques (Part 3) (70.8 MB) 2 - ChatGPT vs Search Engines (33.07 MB) 3 - Artificial Intelligence vs Human Intelligence (25.3 MB) 4 - Creating a ChatGPT account and getting started (51.63 MB) 5 - Update August 2024 (55.64 MB) 6 - Features, Options and Products around GPT models (35.09 MB) 7 - Navigating the OpenAI Website (98.84 MB) 8 - What is a Token and how do Tokens work (63.34 MB) 9 - Prompt Engineering Techniques (Part 1) (107.16 MB) 1 - Introduction and Overview (7.82 MB) 2 - Reinforcement Learning vs traditional Machine Learning (84.44 MB) 3 - Reinforcement Learning - Use Cases (68.66 MB) 4 - Reinforcement Learning - Models and Algorithms (74.07 MB) 1 - Introduction (58.32 MB) 10 - Training an RL Agent with Q-Tables (75.25 MB) 11 - Q-learning explained - the Hyperparameters (107.92 MB) 12 - Q-learning explained - Discretization of the State Space (39.45 MB) 13 - Q-learning explained - the Q-Table (66.28 MB) 14 - Q-learning explained - Visualizing the Q-Table (75.65 MB) 15 - Q-learning explained - Updating the Q-Table (115.95 MB) 16 - Testing the trained Agent (51.07 MB) 17 - Visualizing the trained Agent (31.3 MB) 18 - Improving the Agent Training (Brainstorming) (91.09 MB) 19 - Excursus Randomness and Reproducibility of random events (122.06 MB) 2 - Project Assignment (36.07 MB) 20 - Training and Testing with Reproducibility (random seed) (72.52 MB) 21 - Tuning the Hyperparameters (42.2 MB) 22 - Increasing the number of Training Episodes (50.26 MB) 23 - Visualizing the Training Process and Performance Plateaus (78.41 MB) 24 - Increasing the State Space Discretization (78.48 MB) 25 - Conclusion and Outlook (38.66 MB) 3 - One Random Episode with Human Rendering (60.75 MB) 4 - Defining the maximum number of steps per Episode (36.66 MB) 5 - The code explained - line for line (77.46 MB) 6 - Running multiple random Episodes with human rendering (89.91 MB) 7 - Performance Measurement and Success Evaluation (104.77 MB) 8 - Running multiple Episodes without human Rendering (65.49 MB) 9 - Excursus RGB Rendering with Visualization (49.22 MB) 1 - Introduction (53.13 MB) 10 - SavingLoading and Testing a trained Agent (50.93 MB) 11 - The trained Agent live in Action (20.6 MB) 2 - One Random Episode with Human Rendering (80.14 MB) 3 - Running multiple random Episodes with human rendering (11.04 MB) 4 - Performance Measurement and Success Evaluation (22.54 MB) 5 - Running multiple Episodes without human Rendering (14.29 MB) 6 - Saving and visualizing successful Episodes (24.59 MB) 7 - Creating an appropriate Observation Space for Training (77.47 MB) 8 - State Space Discretization (34.54 MB) 9 - Training a RL Agent for the Lunar Lander (71.44 MB) 1 - Introduction and Assignment (28.92 MB) 10 - Reinforcement Learning with multiple Episodes (95.09 MB) 11 - Hyperparameter Optimization (46.56 MB) 12 - Testing the Agent on new Data (78.21 MB) 13 - The Importance of Trading Costs (38.8 MB) 14 - Modifying the Rewards Function (96.25 MB) 15 - Performance Evaluation and Identifying Overfitting (34.37 MB) 2 - Loading and Preparing the Dataset (22.71 MB) 3 - Splitting into Training and Test Set (20 MB) 4 - Discretization and Quantile Binning (Part 1) (70.3 MB) 5 - Discretization and Quantile Binning (Part 2) (35.99 MB) 6 - Discretization and Quantile Binning (Part 3) (67.52 MB) 7 - Trading Profits and Losses (47.45 MB) 8 - Introduction to Agent Training (one Episode) (61.02 MB) 9 - Training of an Algo Trading Agent - explained (120.11 MB)
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