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[Udemy] Financial Engineering and Artificial Intelligence in Python (2020) [En]
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[Udemy] Financial Engineering and Artificial Intelligence in Python (2020) [En]
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2021-04-14
最近下载:
2025-03-13
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文件列表
11. Setting Up Your Environment FAQ/1. Windows-Focused Environment Setup 2018.mp4
189.4 MB
11. Setting Up Your Environment FAQ/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
157.9 MB
3. Time Series Analysis/18. ARIMA in Code (pt 1).mp4
142.0 MB
3. Time Series Analysis/28. ARIMA in Code (pt 3).mp4
117.4 MB
3. Time Series Analysis/27. ARIMA in Code (pt 2).mp4
115.1 MB
13. Effective Learning Strategies for Machine Learning FAQ/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4
113.4 MB
13. Effective Learning Strategies for Machine Learning FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
110.8 MB
6. VIP The Basics of Reinforcement Learning/2. Elements of a Reinforcement Learning Problem.mp4
110.2 MB
7. VIP Reinforcement Learning for Algorithmic Trading/5. Q-Learning for Algorithmic Trading in Code.mp4
108.1 MB
9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/5. HMM for Modeling Volatility Clustering in Code.mp4
106.9 MB
8. VIP Statistical Factor Models and Unsupervised Machine Learning/4. Statistical Factor Models (Code).mp4
106.0 MB
4. Portfolio Optimization and CAPM/8. Visualizing Random Portfolios and Monte Carlo Simulation (pt 2).mp4
93.0 MB
13. Effective Learning Strategies for Machine Learning FAQ/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4
83.5 MB
2. Financial Basics/5. Understanding Financial Data (Code).mp4
79.3 MB
4. Portfolio Optimization and CAPM/7. Visualizing Random Portfolios and Monte Carlo Simulation (pt 1).mp4
77.2 MB
8. VIP Statistical Factor Models and Unsupervised Machine Learning/3. Statistical Factor Models (Advanced).mp4
76.7 MB
12. Extra Help With Python Coding for Beginners FAQ/1. How to Code by Yourself (part 1).mp4
75.4 MB
3. Time Series Analysis/3. Random Walk Hypothesis.mp4
74.9 MB
5. VIP Algorithmic Trading/6. Machine Learning-Based Trading Strategy in Code.mp4
72.9 MB
12. Extra Help With Python Coding for Beginners FAQ/3. Proof that using Jupyter Notebook is the same as not using it.mp4
72.9 MB
5. VIP Algorithmic Trading/4. Trend-Following Strategy in Code (pt 2).mp4
72.5 MB
6. VIP The Basics of Reinforcement Learning/11. Q-Learning.mp4
70.2 MB
9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/4. HMM Tasks and the Viterbi Algorithm.mp4
68.2 MB
3. Time Series Analysis/20. Stationarity Code.mp4
67.7 MB
5. VIP Algorithmic Trading/3. Trend-Following Strategy in Code (pt 1).mp4
66.7 MB
8. VIP Statistical Factor Models and Unsupervised Machine Learning/1. Statistical Factor Models (Beginner).mp4
66.5 MB
2. Financial Basics/3. Getting Financial Data (Code).mp4
65.7 MB
2. Financial Basics/19. Statistical Testing.mp4
63.6 MB
3. Time Series Analysis/10. Simple Exponential Smoothing for Forecasting (Code).mp4
62.0 MB
6. VIP The Basics of Reinforcement Learning/9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4
60.0 MB
5. VIP Algorithmic Trading/2. Trend-Following Strategy.mp4
58.6 MB
7. VIP Reinforcement Learning for Algorithmic Trading/2. Trend-Following Strategy Revisited (Code).mp4
58.4 MB
3. Time Series Analysis/6. Simple Moving Average (Code).mp4
58.3 MB
3. Time Series Analysis/2. Efficient Market Hypothesis.mp4
57.4 MB
3. Time Series Analysis/8. Exponentially-Weighted Moving Average (Code).mp4
57.0 MB
3. Time Series Analysis/15. Autoregressive Models - AR(p).mp4
56.3 MB
4. Portfolio Optimization and CAPM/13. Mean-Variance Optimization And The Efficient Frontier in Code.mp4
56.0 MB
3. Time Series Analysis/14. Holt-Winters (Code).mp4
55.0 MB
4. Portfolio Optimization and CAPM/20. Capital Asset Pricing Model (CAPM).mp4
54.8 MB
3. Time Series Analysis/19. Stationarity.mp4
53.5 MB
2. Financial Basics/15. The t-Distribution (Code).mp4
53.3 MB
6. VIP The Basics of Reinforcement Learning/4. Markov Decision Processes (MDPs).mp4
53.2 MB
7. VIP Reinforcement Learning for Algorithmic Trading/1. Trend-Following Strategy with Reinforcement Learning API.mp4
52.0 MB
9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/1. Why Sequence Models (pt 1).mp4
51.9 MB
12. Extra Help With Python Coding for Beginners FAQ/2. How to Code by Yourself (part 2).mp4
51.6 MB
3. Time Series Analysis/13. Holt-Winters (Theory).mp4
51.2 MB
3. Time Series Analysis/29. ACF and PACF for Stock Returns.mp4
51.1 MB
4. Portfolio Optimization and CAPM/21. Problems with Markowitz Portfolio Theory and Robust Estimation.mp4
50.4 MB
6. VIP The Basics of Reinforcement Learning/6. Value Functions and the Bellman Equation.mp4
50.3 MB
2. Financial Basics/9. Adjusted Close, Stock Splits, and Dividends.mp4
49.7 MB
3. Time Series Analysis/26. Model Selection, AIC and BIC.mp4
49.6 MB
1. Welcome/1. Introduction and Outline.mp4
49.1 MB
2. Financial Basics/24. Alpha and Beta (Code).mp4
48.0 MB
2. Financial Basics/11. Back to Returns (Code).mp4
47.9 MB
6. VIP The Basics of Reinforcement Learning/3. States, Actions, Rewards, Policies.mp4
46.5 MB
1. Welcome/2. Where to get the code.mp4
46.4 MB
4. Portfolio Optimization and CAPM/17. Maximum Sharpe Ratio in Code.mp4
45.7 MB
6. VIP The Basics of Reinforcement Learning/8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4
44.9 MB
3. Time Series Analysis/17. ARIMA.mp4
44.7 MB
3. Time Series Analysis/23. ACF and PACF in Code (pt 1).mp4
44.4 MB
2. Financial Basics/20. Statistical Testing (Code).mp4
44.0 MB
2. Financial Basics/2. Getting Financial Data.mp4
43.9 MB
6. VIP The Basics of Reinforcement Learning/10. Epsilon-Greedy.mp4
43.7 MB
9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/2. Why Sequence Models (pt 2).mp4
43.1 MB
6. VIP The Basics of Reinforcement Learning/1. Reinforcement Learning Section Introduction.mp4
42.8 MB
3. Time Series Analysis/25. Auto ARIMA and SARIMAX.mp4
42.6 MB
8. VIP Statistical Factor Models and Unsupervised Machine Learning/2. Statistical Factor Models (Intermediate).mp4
42.5 MB
6. VIP The Basics of Reinforcement Learning/12. How to Learn Reinforcement Learning.mp4
42.4 MB
3. Time Series Analysis/30. Forecasting.mp4
41.1 MB
2. Financial Basics/22. Covariance and Correlation (Code).mp4
40.9 MB
2. Financial Basics/17. Confidence Intervals.mp4
40.7 MB
14. Appendix FAQ Finale/2. BONUS Where to get discount coupons and FREE deep learning material.mp4
39.7 MB
4. Portfolio Optimization and CAPM/18. Portfolio with a Risk-Free Asset and Tangency Portfolio.mp4
39.7 MB
3. Time Series Analysis/7. Exponentially-Weighted Moving Average (Theory).mp4
39.6 MB
2. Financial Basics/7. Dealing with Missing Data (Code).mp4
39.5 MB
4. Portfolio Optimization and CAPM/16. Sharpe Ratio.mp4
39.4 MB
9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/3. HMM Parameters.mp4
39.3 MB
3. Time Series Analysis/21. ACF (Autocorrelation Function).mp4
39.2 MB
4. Portfolio Optimization and CAPM/5. Describing a Portfolio (pt 1).mp4
38.3 MB
3. Time Series Analysis/9. Simple Exponential Smoothing for Forecasting (Theory).mp4
38.1 MB
3. Time Series Analysis/24. ACF and PACF in Code (pt 2).mp4
37.1 MB
2. Financial Basics/13. QQ-Plots (Code).mp4
37.0 MB
13. Effective Learning Strategies for Machine Learning FAQ/1. How to Succeed in this Course (Long Version).mp4
37.0 MB
2. Financial Basics/16. Skewness and Kurtosis.mp4
36.4 MB
2. Financial Basics/26. Mixture of Gaussians (Code).mp4
35.2 MB
5. VIP Algorithmic Trading/5. Machine Learning-Based Trading Strategy.mp4
34.9 MB
4. Portfolio Optimization and CAPM/4. Why Diversify.mp4
34.8 MB
5. VIP Algorithmic Trading/8. Using a Random Forest Classifier for Machine Learning-Based Trading.mp4
34.6 MB
3. Time Series Analysis/11. Holt's Linear Trend Model (Theory).mp4
34.6 MB
2. Financial Basics/21. Covariance and Correlation.mp4
34.5 MB
6. VIP The Basics of Reinforcement Learning/7. What does it mean to “learn”.mp4
34.3 MB
4. Portfolio Optimization and CAPM/9. Maximum and Minimum Portfolio Return.mp4
34.3 MB
7. VIP Reinforcement Learning for Algorithmic Trading/4. Representing States.mp4
34.2 MB
3. Time Series Analysis/1. Time Series Analysis Section Introduction.mp4
33.4 MB
4. Portfolio Optimization and CAPM/11. Mean-Variance Optimization.mp4
33.2 MB
3. Time Series Analysis/4. The Naive Forecast.mp4
32.5 MB
4. Portfolio Optimization and CAPM/12. The Efficient Frontier.mp4
32.2 MB
4. Portfolio Optimization and CAPM/3. What is Risk.mp4
32.0 MB
5. VIP Algorithmic Trading/9. Algorithmic Trading Section Summary.mp4
31.4 MB
7. VIP Reinforcement Learning for Algorithmic Trading/3. Q-Learning in an Algorithmic Trading Context.mp4
31.1 MB
2. Financial Basics/25. Mixture of Gaussians.mp4
30.8 MB
2. Financial Basics/8. Returns.mp4
30.7 MB
2. Financial Basics/1. Financial Basics Section Introduction.mp4
30.3 MB
2. Financial Basics/23. Alpha and Beta.mp4
30.2 MB
2. Financial Basics/4. Understanding Financial Data.mp4
29.9 MB
2. Financial Basics/6. Dealing with Missing Data.mp4
29.7 MB
4. Portfolio Optimization and CAPM/10. Maximum and Minimum Portfolio Return in Code.mp4
29.3 MB
3. Time Series Analysis/22. PACF (Partial Autocorrelation Funtion).mp4
27.4 MB
5. VIP Algorithmic Trading/7. Classification-Based Trading Strategy in Code.mp4
26.3 MB
1. Welcome/4. How to Practice.mp4
25.7 MB
4. Portfolio Optimization and CAPM/1. Portfolio Optimization Section Introduction.mp4
25.5 MB
1. Welcome/3. Scope of the course.mp4
24.8 MB
6. VIP The Basics of Reinforcement Learning/5. The Return.mp4
24.7 MB
4. Portfolio Optimization and CAPM/6. Describing a Portfolio (pt 2).mp4
23.9 MB
2. Financial Basics/10. Adjusted Close (Code).mp4
22.0 MB
2. Financial Basics/12. QQ-Plots.mp4
21.7 MB
3. Time Series Analysis/5. Simple Moving Average (Theory).mp4
20.8 MB
1. Welcome/5. Warmup (Optional).mp4
20.7 MB
2. Financial Basics/14. The t-Distribution.mp4
20.6 MB
3. Time Series Analysis/12. Holt's Linear Trend Model (Code).mp4
19.5 MB
2. Financial Basics/27. Volatility Clustering.mp4
19.4 MB
3. Time Series Analysis/31. Time Series Analysis Section Conclusion.mp4
19.0 MB
4. Portfolio Optimization and CAPM/22. Portfolio Optimization Section Conclusion.mp4
18.3 MB
14. Appendix FAQ Finale/1. What is the Appendix.mp4
17.2 MB
2. Financial Basics/31. Suggestion Box.mp4
16.9 MB
5. VIP Algorithmic Trading/1. Algorithmic Trading Section Introduction.mp4
14.7 MB
4. Portfolio Optimization and CAPM/15. Global Minimum Variance (GMV) Portfolio in Code.mp4
14.3 MB
4. Portfolio Optimization and CAPM/19. Risk-Free Asset and Tangency Portfolio in Code.mp4
14.2 MB
10. Extras/2. VIP Finance Enthusiasts, Beware of Marketers!.mp4
14.2 MB
2. Financial Basics/18. Confidence Intervals (Code).mp4
12.9 MB
2. Financial Basics/29. Price Simulation (Code).mp4
12.8 MB
2. Financial Basics/28. Price Simulation.mp4
12.6 MB
4. Portfolio Optimization and CAPM/2. The S&P500.mp4
12.2 MB
3. Time Series Analysis/16. Moving Average Models - MA(q).mp4
11.5 MB
2. Financial Basics/30. Financial Basics Section Summary.mp4
10.5 MB
4. Portfolio Optimization and CAPM/14. Global Minimum Variance (GMV) Portfolio.mp4
9.0 MB
13. Effective Learning Strategies for Machine Learning FAQ/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt
32.7 kB
6. VIP The Basics of Reinforcement Learning/2. Elements of a Reinforcement Learning Problem.srt
26.5 kB
8. VIP Statistical Factor Models and Unsupervised Machine Learning/3. Statistical Factor Models (Advanced).srt
26.0 kB
3. Time Series Analysis/18. ARIMA in Code (pt 1).srt
25.1 kB
9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/5. HMM for Modeling Volatility Clustering in Code.srt
24.7 kB
13. Effective Learning Strategies for Machine Learning FAQ/4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt
24.1 kB
12. Extra Help With Python Coding for Beginners FAQ/1. How to Code by Yourself (part 1).srt
23.2 kB
8. VIP Statistical Factor Models and Unsupervised Machine Learning/1. Statistical Factor Models (Beginner).srt
21.7 kB
2. Financial Basics/19. Statistical Testing.srt
21.3 kB
11. Setting Up Your Environment FAQ/1. Windows-Focused Environment Setup 2018.srt
20.2 kB
9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/4. HMM Tasks and the Viterbi Algorithm.srt
19.7 kB
3. Time Series Analysis/3. Random Walk Hypothesis.srt
19.6 kB
9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/1. Why Sequence Models (pt 1).srt
19.2 kB
8. VIP Statistical Factor Models and Unsupervised Machine Learning/4. Statistical Factor Models (Code).srt
19.0 kB
7. VIP Reinforcement Learning for Algorithmic Trading/5. Q-Learning for Algorithmic Trading in Code.srt
18.9 kB
4. Portfolio Optimization and CAPM/8. Visualizing Random Portfolios and Monte Carlo Simulation (pt 2).srt
18.8 kB
3. Time Series Analysis/28. ARIMA in Code (pt 3).srt
18.5 kB
6. VIP The Basics of Reinforcement Learning/11. Q-Learning.srt
18.5 kB
5. VIP Algorithmic Trading/2. Trend-Following Strategy.srt
18.4 kB
13. Effective Learning Strategies for Machine Learning FAQ/3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt
17.2 kB
3. Time Series Analysis/15. Autoregressive Models - AR(p).srt
17.1 kB
3. Time Series Analysis/27. ARIMA in Code (pt 2).srt
17.1 kB
3. Time Series Analysis/19. Stationarity.srt
16.7 kB
4. Portfolio Optimization and CAPM/7. Visualizing Random Portfolios and Monte Carlo Simulation (pt 1).srt
16.6 kB
2. Financial Basics/9. Adjusted Close, Stock Splits, and Dividends.srt
16.6 kB
3. Time Series Analysis/2. Efficient Market Hypothesis.srt
16.5 kB
4. Portfolio Optimization and CAPM/20. Capital Asset Pricing Model (CAPM).srt
16.4 kB
9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/2. Why Sequence Models (pt 2).srt
16.4 kB
7. VIP Reinforcement Learning for Algorithmic Trading/1. Trend-Following Strategy with Reinforcement Learning API.srt
16.1 kB
2. Financial Basics/5. Understanding Financial Data (Code).srt
15.5 kB
3. Time Series Analysis/13. Holt-Winters (Theory).srt
15.4 kB
6. VIP The Basics of Reinforcement Learning/9. Solving the Bellman Equation with Reinforcement Learning (pt 2).srt
15.1 kB
13. Effective Learning Strategies for Machine Learning FAQ/1. How to Succeed in this Course (Long Version).srt
15.1 kB
3. Time Series Analysis/8. Exponentially-Weighted Moving Average (Code).srt
15.0 kB
3. Time Series Analysis/7. Exponentially-Weighted Moving Average (Theory).srt
14.9 kB
11. Setting Up Your Environment FAQ/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt
14.5 kB
12. Extra Help With Python Coding for Beginners FAQ/3. Proof that using Jupyter Notebook is the same as not using it.srt
14.4 kB
3. Time Series Analysis/9. Simple Exponential Smoothing for Forecasting (Theory).srt
14.2 kB
3. Time Series Analysis/17. ARIMA.srt
14.1 kB
2. Financial Basics/17. Confidence Intervals.srt
14.0 kB
3. Time Series Analysis/26. Model Selection, AIC and BIC.srt
13.8 kB
12. Extra Help With Python Coding for Beginners FAQ/2. How to Code by Yourself (part 2).srt
13.5 kB
8. VIP Statistical Factor Models and Unsupervised Machine Learning/2. Statistical Factor Models (Intermediate).srt
13.4 kB
3. Time Series Analysis/21. ACF (Autocorrelation Function).srt
13.3 kB
6. VIP The Basics of Reinforcement Learning/4. Markov Decision Processes (MDPs).srt
13.0 kB
3. Time Series Analysis/10. Simple Exponential Smoothing for Forecasting (Code).srt
12.9 kB
6. VIP The Basics of Reinforcement Learning/6. Value Functions and the Bellman Equation.srt
12.9 kB
4. Portfolio Optimization and CAPM/9. Maximum and Minimum Portfolio Return.srt
12.8 kB
6. VIP The Basics of Reinforcement Learning/8. Solving the Bellman Equation with Reinforcement Learning (pt 1).srt
12.7 kB
4. Portfolio Optimization and CAPM/18. Portfolio with a Risk-Free Asset and Tangency Portfolio.srt
12.7 kB
1. Welcome/2. Where to get the code.srt
12.7 kB
9. VIP Regime Detection and Sequence Modeling with Hidden Markov Models/3. HMM Parameters.srt
12.6 kB
4. Portfolio Optimization and CAPM/5. Describing a Portfolio (pt 1).srt
12.6 kB
3. Time Series Analysis/25. Auto ARIMA and SARIMAX.srt
12.6 kB
4. Portfolio Optimization and CAPM/21. Problems with Markowitz Portfolio Theory and Robust Estimation.srt
12.5 kB
3. Time Series Analysis/30. Forecasting.srt
12.4 kB
5. VIP Algorithmic Trading/4. Trend-Following Strategy in Code (pt 2).srt
12.3 kB
2. Financial Basics/8. Returns.srt
12.0 kB
6. VIP The Basics of Reinforcement Learning/3. States, Actions, Rewards, Policies.srt
11.9 kB
4. Portfolio Optimization and CAPM/13. Mean-Variance Optimization And The Efficient Frontier in Code.srt
11.5 kB
2. Financial Basics/21. Covariance and Correlation.srt
11.1 kB
3. Time Series Analysis/20. Stationarity Code.srt
11.0 kB
7. VIP Reinforcement Learning for Algorithmic Trading/2. Trend-Following Strategy Revisited (Code).srt
10.8 kB
4. Portfolio Optimization and CAPM/4. Why Diversify.srt
10.8 kB
2. Financial Basics/15. The t-Distribution (Code).srt
10.7 kB
2. Financial Basics/24. Alpha and Beta (Code).srt
10.6 kB
5. VIP Algorithmic Trading/6. Machine Learning-Based Trading Strategy in Code.srt
10.6 kB
2. Financial Basics/16. Skewness and Kurtosis.srt
10.6 kB
5. VIP Algorithmic Trading/5. Machine Learning-Based Trading Strategy.srt
10.5 kB
3. Time Series Analysis/11. Holt's Linear Trend Model (Theory).srt
10.3 kB
4. Portfolio Optimization and CAPM/11. Mean-Variance Optimization.srt
10.3 kB
4. Portfolio Optimization and CAPM/16. Sharpe Ratio.srt
10.2 kB
2. Financial Basics/2. Getting Financial Data.srt
10.2 kB
2. Financial Basics/13. QQ-Plots (Code).srt
10.2 kB
3. Time Series Analysis/14. Holt-Winters (Code).srt
10.1 kB
1. Welcome/1. Introduction and Outline.srt
9.8 kB
7. VIP Reinforcement Learning for Algorithmic Trading/4. Representing States.srt
9.8 kB
4. Portfolio Optimization and CAPM/12. The Efficient Frontier.srt
9.8 kB
2. Financial Basics/3. Getting Financial Data (Code).srt
9.7 kB
3. Time Series Analysis/6. Simple Moving Average (Code).srt
9.7 kB
5. VIP Algorithmic Trading/3. Trend-Following Strategy in Code (pt 1).srt
9.6 kB
4. Portfolio Optimization and CAPM/3. What is Risk.srt
9.6 kB
3. Time Series Analysis/23. ACF and PACF in Code (pt 1).srt
9.6 kB
3. Time Series Analysis/1. Time Series Analysis Section Introduction.srt
9.6 kB
7. VIP Reinforcement Learning for Algorithmic Trading/3. Q-Learning in an Algorithmic Trading Context.srt
9.5 kB
2. Financial Basics/23. Alpha and Beta.srt
9.5 kB
3. Time Series Analysis/4. The Naive Forecast.srt
9.4 kB
2. Financial Basics/25. Mixture of Gaussians.srt
9.4 kB
2. Financial Basics/11. Back to Returns (Code).srt
9.3 kB
2. Financial Basics/20. Statistical Testing (Code).srt
9.3 kB
2. Financial Basics/7. Dealing with Missing Data (Code).srt
9.2 kB
6. VIP The Basics of Reinforcement Learning/7. What does it mean to “learn”.srt
9.1 kB
6. VIP The Basics of Reinforcement Learning/1. Reinforcement Learning Section Introduction.srt
8.9 kB
3. Time Series Analysis/29. ACF and PACF for Stock Returns.srt
8.7 kB
4. Portfolio Optimization and CAPM/17. Maximum Sharpe Ratio in Code.srt
8.5 kB
2. Financial Basics/26. Mixture of Gaussians (Code).srt
8.4 kB
3. Time Series Analysis/24. ACF and PACF in Code (pt 2).srt
8.2 kB
3. Time Series Analysis/22. PACF (Partial Autocorrelation Funtion).srt
8.2 kB
4. Portfolio Optimization and CAPM/6. Describing a Portfolio (pt 2).srt
8.1 kB
14. Appendix FAQ Finale/2. BONUS Where to get discount coupons and FREE deep learning material.srt
8.0 kB
2. Financial Basics/6. Dealing with Missing Data.srt
8.0 kB
6. VIP The Basics of Reinforcement Learning/12. How to Learn Reinforcement Learning.srt
7.7 kB
5. VIP Algorithmic Trading/9. Algorithmic Trading Section Summary.srt
7.7 kB
6. VIP The Basics of Reinforcement Learning/10. Epsilon-Greedy.srt
7.6 kB
2. Financial Basics/1. Financial Basics Section Introduction.srt
7.6 kB
2. Financial Basics/12. QQ-Plots.srt
7.4 kB
2. Financial Basics/22. Covariance and Correlation (Code).srt
7.3 kB
2. Financial Basics/4. Understanding Financial Data.srt
6.8 kB
6. VIP The Basics of Reinforcement Learning/5. The Return.srt
6.5 kB
4. Portfolio Optimization and CAPM/10. Maximum and Minimum Portfolio Return in Code.srt
5.9 kB
3. Time Series Analysis/5. Simple Moving Average (Theory).srt
5.9 kB
5. VIP Algorithmic Trading/8. Using a Random Forest Classifier for Machine Learning-Based Trading.srt
5.7 kB
1. Welcome/5. Warmup (Optional).srt
5.6 kB
3. Time Series Analysis/31. Time Series Analysis Section Conclusion.srt
5.4 kB
1. Welcome/4. How to Practice.srt
5.3 kB
2. Financial Basics/14. The t-Distribution.srt
5.2 kB
4. Portfolio Optimization and CAPM/1. Portfolio Optimization Section Introduction.srt
4.9 kB
1. Welcome/3. Scope of the course.srt
4.9 kB
2. Financial Basics/31. Suggestion Box.srt
4.8 kB
2. Financial Basics/10. Adjusted Close (Code).srt
4.7 kB
5. VIP Algorithmic Trading/7. Classification-Based Trading Strategy in Code.srt
4.3 kB
3. Time Series Analysis/16. Moving Average Models - MA(q).srt
4.3 kB
2. Financial Basics/28. Price Simulation.srt
4.1 kB
2. Financial Basics/27. Volatility Clustering.srt
4.0 kB
14. Appendix FAQ Finale/1. What is the Appendix.srt
3.9 kB
5. VIP Algorithmic Trading/1. Algorithmic Trading Section Introduction.srt
3.7 kB
3. Time Series Analysis/12. Holt's Linear Trend Model (Code).srt
3.5 kB
4. Portfolio Optimization and CAPM/2. The S&P500.srt
3.4 kB
2. Financial Basics/29. Price Simulation (Code).srt
3.2 kB
2. Financial Basics/30. Financial Basics Section Summary.srt
3.1 kB
4. Portfolio Optimization and CAPM/22. Portfolio Optimization Section Conclusion.srt
3.0 kB
2. Financial Basics/18. Confidence Intervals (Code).srt
2.9 kB
10. Extras/2. VIP Finance Enthusiasts, Beware of Marketers!.srt
2.9 kB
4. Portfolio Optimization and CAPM/19. Risk-Free Asset and Tangency Portfolio in Code.srt
2.6 kB
4. Portfolio Optimization and CAPM/15. Global Minimum Variance (GMV) Portfolio in Code.srt
2.5 kB
4. Portfolio Optimization and CAPM/14. Global Minimum Variance (GMV) Portfolio.srt
2.4 kB
10. Extras/1. Colab Notebooks.html
256 Bytes
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