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 скачать 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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https://ddownload.com/hqbzjijclfhg/Udemy_Reinforcement_Learning_for_Algorithmic_Trading_with_Python.part1.rar
https://ddownload.com/to5484m740ev/Udemy_Reinforcement_Learning_for_Algorithmic_Trading_with_Python.part2.rar
https://ddownload.com/u02y1kyhwhrv/Udemy_Reinforcement_Learning_for_Algorithmic_Trading_with_Python.part3.rar

https://rapidgator.net/file/0570e543c5a0e327a53b7d0f3d901ae2/Udemy_Reinforcement_Learning_for_Algorithmic_Trading_with_Python.part1.rar
https://rapidgator.net/file/54fcf898663c2cc1d71c444d4e4aed3e/Udemy_Reinforcement_Learning_for_Algorithmic_Trading_with_Python.part2.rar
https://rapidgator.net/file/22920a358cd920032e36884865b85078/Udemy_Reinforcement_Learning_for_Algorithmic_Trading_with_Python.part3.rar

https://turbobit.net/xwraxca1nehx/Udemy_Reinforcement_Learning_for_Algorithmic_Trading_with_Python.part1.rar.html
https://turbobit.net/kk9aj9wpjcif/Udemy_Reinforcement_Learning_for_Algorithmic_Trading_with_Python.part2.rar.html
https://turbobit.net/y0avwbcnnedp/Udemy_Reinforcement_Learning_for_Algorithmic_Trading_with_Python.part3.rar.html