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Part 01-Module 01-Lesson 06_Data Processing/14. Eddy Deven V2-g7zJV-Ontbo.mp4 62.8 MBPart 02-Module 01-Lesson 01_Welcome To Term II/04. NewsRoom Liz V2-Os881EhJv68.mp4 58.9 MBPart 02-Module 01-Lesson 01_Welcome To Term II/05. AITND Term II Interview W Justin V2 V2-JOkwa1brNX8.mp4 50.6 MBPart 01-Module 01-Lesson 09_Project 1 Trading with Momentum/04. Eddy Thomas 02 AI And Finanace V2-8Hna_hR_N7c.mp4 38.8 MBPart 02-Module 01-Lesson 05_Financial Statements/03. M5 SC 15 10Ks Walkthrough V1-0ytyZ4LVG6s.mp4 38.7 MBPart 01-Module 02-Lesson 07_Project 2 Breakout Strategy/05. Eddy Thomas 03 Jobs And Interviews V2-5W9XsgyxYHE.mp4 35.4 MBPart 07-Module 01-Lesson 05_Introduction to Kalman Filters/25. Kalman Filter Code Solution - Artificial Intelligence for Robotics-X7cixvcogl8.mp4 35.4 MBPart 02-Module 04-Lesson 01_Strengthen Your Online Presence Using LinkedIn/02. Meet Chris-0ccflD9x5WU.mp4 34.1 MBPart 02-Module 02-Lesson 03_Deep Learning with PyTorch/24. PyTorch - Part 8-S9F7MtJ5jls.mp4 30.9 MBPart 02-Module 05-Lesson 02_Optimization with Transaction Costs/16. NewsRoom Juan V2-DpO73QaXaOY.mp4 27.2 MBPart 02-Module 01-Lesson 06_Basic NLP Analysis/06. AIT M5L5 05 Frequency Reweighting V2-X-Cf2Uj7tH4.mp4 26.6 MBPart 02-Module 04-Lesson 02_Optimize Your GitHub Profile/14. Interview with Art - Part 3-M6PKr3S1rPg.mp4 26.3 MBPart 02-Module 05-Lesson 01_Intro to Backtesting/10. NewsRoom Liz Short V2-vqHsk3hjBLU.mp4 25.8 MBPart 01-Module 01-Lesson 01_Welcome to the Nanodegree Program/12. Eddy Thomas 01 Quants V2-ZRzhyaqz7I0.mp4 25.0 MBPart 03-Module 01-Lesson 02_Data Types and Operators/19. String Methods-Bv7CAxVOONs.mp4 24.9 MBPart 01-Module 04-Lesson 01_Factors/12. Zipline Pipeline SC V1-DHTwIwVk_sc.mp4 24.6 MBPart 07-Module 01-Lesson 03_Clustering/13. Sklearn-3zHUAXcoZ7c.mp4 24.4 MBPart 01-Module 03-Lesson 04_Portfolio Optimization/12. L4 13 Limitations V2-UbbZa7-3iuk.mp4 24.3 MBPart 02-Module 05-Lesson 04_Project 8 Backtesting/03. AITND Finish V2-g-a4ZNIPQqw.mp4 24.2 MBPart 02-Module 03-Lesson 05_Feature Engineering/10. M7L5 22 V1-34bV5mYUJAI.mp4 23.8 MBPart 02-Module 01-Lesson 05_Financial Statements/12. M5 SC 7 Metacharacters Part 2 V1-KK1xo8GDfvE.mp4 23.7 MBPart 06-Module 01-Lesson 06_Conditional Probability/03. Medical Example 2-FV_hc3MzS_8.mp4 23.1 MBPart 02-Module 03-Lesson 05_Feature Engineering/09. M7L5 18 V1-7LESwsbt70s.mp4 23.0 MBPart 06-Module 01-Lesson 09_Normal Distribution Theory/01. Maximum Probability-b2zvrFL8AUw.mp4 23.0 MBPart 02-Module 03-Lesson 02_Decision Trees/02. MLND SL DT 00 Intro V2-l34ijtQhVNk.mp4 22.7 MBPart 07-Module 01-Lesson 04_Decision Trees/01. MLND SL DT 00 Intro V2-l34ijtQhVNk.mp4 22.7 MBPart 03-Module 01-Lesson 02_Data Types and Operators/10. Boolean Comparison and Logical Operators-iNNsUJIDtVU.mp4 22.7 MBPart 02-Module 05-Lesson 01_Intro to Backtesting/03. M8L1 07 Backtest Validity V5-KTlrel9p6Q0.mp4 22.6 MBPart 02-Module 02-Lesson 03_Deep Learning with PyTorch/12. PyTorch V2 Part 3 Solution V2-zBWlOeX2sQM.mp4 22.3 MBPart 07-Module 01-Lesson 02_Naive Bayes/04. SL NB 03 Guess The Person Now V1 V2-pQgO1KF90yU.mp4 22.1 MBPart 03-Module 01-Lesson 02_Data Types and Operators/08. Whitespace-UxkIwcOczQQ.mp4 22.0 MBPart 04-Module 01-Lesson 04_Linear Transformation and Matrices/09. Linear Transformations 1-99jYIxBRDww.mp4 21.8 MBPart 02-Module 04-Lesson 01_Strengthen Your Online Presence Using LinkedIn/03. Elevator Pitch-S-nAHPrkQrQ.mp4 21.6 MBPart 02-Module 01-Lesson 05_Financial Statements/02. AIT M5L4A 02 Financial Statement V6-XYff0ROHzWo.mp4 21.4 MBPart 04-Module 01-Lesson 04_Linear Transformation and Matrices/11. Linear Transformations 3-g_yTyRwMzXU.mp4 21.1 MBPart 03-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.mp4 20.9 MBPart 01-Module 04-Lesson 03_Risk Factor Models/18. MV When You Dont Believe In Yourself 1 V1-rjCr-Z7UhZE.mp4 20.8 MBPart 01-Module 04-Lesson 01_Factors/02. M4 L1A 02 Intro V2-W7_llXQ2GhA.mp4 20.7 MBPart 02-Module 01-Lesson 03_Text Processing/06. Cleaning-qawXp9DPV6I.mp4 20.5 MBPart 02-Module 05-Lesson 04_Project 8 Backtesting/01. NewsRoom Eddy 1 V2-9MlGvKWQn_o.mp4 20.2 MBPart 03-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.mp4 19.9 MBPart 01-Module 01-Lesson 06_Data Processing/11. M1L4 13 Exchange Traded Funds V4-Zx7v5GCfpvI.mp4 19.8 MBPart 02-Module 02-Lesson 03_Deep Learning with PyTorch/11. PyTorch V2 Part 3 V1-9ILiZwbi9dA.mp4 19.7 MBPart 03-Module 01-Lesson 03_Control Flow/10. For Loops-UtX0PXSUCdY.mp4 19.3 MBPart 02-Module 02-Lesson 04_Recurrent Neural Networks/20. 07 CharRNN Solution V1-ed33qePHrJM.mp4 19.2 MBPart 01-Module 04-Lesson 08_Advanced Portfolio Optimization/17. MV 12 Embrace The Struggle V2-SGcgOm5kiKU.mp4 19.2 MBPart 03-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.mp4 19.2 MBPart 06-Module 01-Lesson 07_Bayes Rule/02. Cancer Test-CNpSrdnYvbo.mp4 18.9 MBPart 01-Module 01-Lesson 01_Welcome to the Nanodegree Program/08. Jonathan Larkin Careers-QhHNPxM_Ku4.mp4 18.8 MBPart 02-Module 01-Lesson 05_Financial Statements/13. M5 SC 8 Metacharacters Part 3 V1-nDlxRlDUNHk.mp4 18.5 MBPart 02-Module 01-Lesson 06_Basic NLP Analysis/02. AIT M5L5 02 Readability V2-pcB63lIgiQg.mp4 18.5 MBPart 02-Module 01-Lesson 05_Financial Statements/14. M5 SC 9 Substitutions And Flags V1-9pxTGOlkLEY.mp4 18.4 MBPart 02-Module 02-Lesson 03_Deep Learning with PyTorch/25. PyTorch V2 Part 8 Solution V1-4n6T93hKRD4.mp4 18.3 MBPart 02-Module 04-Lesson 01_Strengthen Your Online Presence Using LinkedIn/01. Why Network-exjEm9Paszk.mp4 18.2 MBPart 03-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.mp4 18.2 MBPart 02-Module 03-Lesson 05_Feature Engineering/05. M7L5 6 V1-R8kfSvnHA3k.mp4 18.2 MBPart 02-Module 01-Lesson 01_Welcome To Term II/01. AITND TII 01 Recap Of Term 1 V1-uhIvBfhcyLM.mp4 18.1 MBPart 03-Module 01-Lesson 02_Data Types and Operators/13. Strings-ySZDrs-nNqg.mp4 18.1 MBPart 01-Module 04-Lesson 02_Factor Models and Types of Factors/07. M4 L1B 06 Factor Models In Quant Finance V2-VeM2SudgZqc.mp4 18.1 MBPart 03-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.mp4 17.8 MBPart 02-Module 03-Lesson 05_Feature Engineering/07. M7L5 12 V1-cHU7Sh12eOo.mp4 17.7 MBPart 06-Module 01-Lesson 07_Bayes Rule/20. Bayes Rule Summary-RgXQ8GRsjfc.mp4 17.7 MBPart 03-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.mp4 17.6 MBPart 02-Module 02-Lesson 03_Deep Learning with PyTorch/10. PyTorch V2 Part 2 Solution 2 V1-8KRX7HvqfP0.mp4 17.5 MBPart 01-Module 02-Lesson 04_Time Series Modeling/04. M2L4 05 Advanced Time Series Models V5-cj1RCBTDog8.mp4 17.4 MBPart 06-Module 01-Lesson 05_Binomial Distribution/09. Arrangements-GeINbOOYkF8.mp4 16.7 MBPart 02-Module 02-Lesson 03_Deep Learning with PyTorch/19. Saving Loading Models V1-psmrPu-mseA.mp4 16.7 MBPart 03-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.mp4 16.7 MBPart 02-Module 02-Lesson 03_Deep Learning with PyTorch/17. PyTorch V2 Part 5 Solution V1-AjrXltxqsK4.mp4 16.6 MBPart 06-Module 01-Lesson 06_Conditional Probability/15. Summary-yepMH9VswI8.mp4 16.6 MBPart 02-Module 02-Lesson 04_Recurrent Neural Networks/17. 04 Implementing CharRNN V2-MMtgZXzFB10.mp4 16.5 MBPart 02-Module 03-Lesson 07_Feature Importance/07. L7 HS17 V1-k0vANVo-5Ek.mp4 16.5 MBPart 03-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.mp4 16.5 MBPart 02-Module 02-Lesson 03_Deep Learning with PyTorch/05. PyTorch V2 Part 1 Solution V1-mNJ8CujTtpo.mp4 16.4 MBPart 01-Module 03-Lesson 04_Portfolio Optimization/11. L4 12 Rebalancing Strategies V2-8u5gBx-fYr8.mp4 16.4 MBPart 01-Module 04-Lesson 02_Factor Models and Types of Factors/26. M4 L1B 25 Other Alternative Data V1-hMw3AuPVSSs.mp4 16.2 MBPart 03-Module 01-Lesson 04_Functions/02. Defining Functions-IP_tJYhynbc.mp4 16.2 MBPart 03-Module 01-Lesson 02_Data Types and Operators/08. Números inteiros e floats-MiJ1vfWp-Ts.mp4 16.2 MBPart 03-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.mp4 16.1 MBPart 01-Module 04-Lesson 02_Factor Models and Types of Factors/08. M4 L1B 07 Risk Factors V Alpha Factors V2-9KUpH1MDC1k.mp4 16.0 MBPart 01-Module 04-Lesson 05_Risk Factor Models with PCA/14. PCA Toy Problem SC V1-uyl44T12yU8.mp4 15.9 MBPart 01-Module 02-Lesson 02_Outliers and Filtering/02. M2L2 02 Sources Of Outliers V8-gXKhKQ2_TaA.mp4 15.9 MBPart 01-Module 02-Lesson 05_Volatility/12. M2L5 12 Using Volatility For Equity Trading V5-Vh9ajVRedvY.mp4 15.9 MBPart 02-Module 01-Lesson 05_Financial Statements/18. M5 SC 16 HTML Structure V1-R3QLtHxedXw.mp4 15.8 MBPart 03-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.mp4 15.8 MBPart 01-Module 04-Lesson 02_Factor Models and Types of Factors/25. M4 L1B 24 NLP Used To Enhance Fundamental Analysis V1-9zMWuZ9j7rI.mp4 15.8 MBPart 06-Module 01-Lesson 07_Bayes Rule/03. Prior And Posterior-o2Tpws5C2Eg.mp4 15.7 MBPart 01-Module 04-Lesson 06_Alpha Factors/53. M4 L3a 27 Interlude Pt 3 V2-v6cLkoJhujU.mp4 15.5 MBPart 02-Module 02-Lesson 04_Recurrent Neural Networks/12. 02 Time Series Prediction V2-xV5jHLFfJbQ.mp4 15.5 MBPart 02-Module 05-Lesson 01_Intro to Backtesting/02. M8L1 06 What Is A Backtest V4-q2dW6-ZRaXE.mp4 15.5 MBPart 01-Module 04-Lesson 06_Alpha Factors/52. M4 L3a 26 Interlude Pt 2 V2-1a60RPqhO8k.mp4 15.4 MBPart 02-Module 02-Lesson 05_Embeddings Word2Vec/06. 4 Data Subsampling V1-7SJXv2BQzZA.mp4 15.4 MBPart 02-Module 01-Lesson 05_Financial Statements/09. M5 SC 4 Searching For Simple Patte V1-7RAHoJ34gXI.mp4 15.4 MBPart 02-Module 02-Lesson 03_Deep Learning with PyTorch/20. PyTorch - Part 7-hFu7GTfRWks.mp4 15.3 MBPart 07-Module 01-Lesson 02_Naive Bayes/07. SL NB 06 S False Positives V1 V3-Bg6_Tvcv81A.mp4 15.1 MBPart 02-Module 02-Lesson 05_Embeddings Word2Vec/16. 12 CompleteModel CustomLoss V2-7SqNN_eUAdc.mp4 15.0 MBPart 01-Module 04-Lesson 02_Factor Models and Types of Factors/03. M4 L1B 03 Factor Returns As Latent Variables V3-LpHvJq6XTOQ.mp4 14.9 MBPart 01-Module 01-Lesson 01_Welcome to the Nanodegree Program/02. Jonathan Larkin - What Is A Quant-G22oM0qv0Hs.mp4 14.9 MBPart 01-Module 03-Lesson 04_Portfolio Optimization/10. L4 11 Rebalancing A Portfolio V2-S5SPhBpG3b0.mp4 14.9 MBPart 02-Module 03-Lesson 05_Feature Engineering/06. M7L5 9 V1-x7ON_-QrpHQ.mp4 14.9 MBPart 01-Module 04-Lesson 02_Factor Models and Types of Factors/02. M4 L1B 02 What Is A Factor Model V4-K5QKPwU38Do.mp4 14.9 MBPart 05-Module 01-Lesson 02_NumPy/05. NumPy 2 V1-KR3hHf9Zxxg.mp4 14.9 MBPart 04-Module 01-Lesson 03_Linear Combination/02. Linear Combinations 2-RsKJNDTb8nw.mp4 14.9 MBPart 01-Module 01-Lesson 06_Data Processing/05. M1L4 08 Missing Values V5-XaMaVFUIc_I.mp4 14.9 MBPart 09-Module 01-Lesson 01_Intro to Computer Vision/10. AffdexMe Demo-dpFtXDqakvY.mp4 14.6 MBPart 09-Module 01-Lesson 01_Intro to Computer Vision/06. Vision-based Emotion AI-7nKKWWn1sAc.mp4 14.4 MBPart 02-Module 02-Lesson 05_Embeddings Word2Vec/11. 9 Model Validation Loss V2-GKDCq8J76tM.mp4 14.3 MBPart 02-Module 05-Lesson 01_Intro to Backtesting/04. M8L1 08 Backtest Overfitting V2-MnWHGIiqjns.mp4 14.3 MBPart 02-Module 01-Lesson 05_Financial Statements/10. M5 SC 5 Word Boundaries V1-3dWIHULqKog.mp4 14.3 MBPart 01-Module 04-Lesson 01_Factors/01. M4 L3A 01 Intro To The Factors V2-OqhRUxHf6wo.mp4 14.2 MBPart 01-Module 04-Lesson 06_Alpha Factors/05. M4 L3a 04 Researching Alphas From Academic Papers V4-te0UTxemLBE.mp4 14.2 MBPart 04-Module 01-Lesson 04_Linear Transformation and Matrices/10. Linear Transformations 2-imtEd8M6__s.mp4 14.1 MBPart 03-Module 01-Lesson 02_Data Types and Operators/25. L2 06 Lists Methods V1-tz2Ja1Eaeqo.mp4 14.0 MBPart 07-Module 01-Lesson 05_Introduction to Kalman Filters/23. Kalman Filter Code - Artificial Intelligence for Robotics-3xBycKfnCOQ.mp4 13.9 MBPart 03-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.mp4 13.9 MBPart 03-Module 01-Lesson 03_Control Flow/25. Break and Continue-F6qJAv9ts9Y.mp4 13.9 MBPart 02-Module 04-Lesson 02_Optimize Your GitHub Profile/10. Interview with Art - Part 2-Vvzl2J5K7-Y.mp4 13.8 MBPart 02-Module 03-Lesson 02_Decision Trees/17. Maximizing Information Gain-3FgJOpKfdY8.mp4 13.8 MBPart 07-Module 01-Lesson 04_Decision Trees/14. Maximizing Information Gain-3FgJOpKfdY8.mp4 13.8 MBPart 02-Module 01-Lesson 05_Financial Statements/23. M5 SC 14 Searching The Parse Tree Part 3 V1-PR--1dLqcTM.mp4 13.7 MBPart 01-Module 04-Lesson 06_Alpha Factors/50. M4 L3a 23 Summary V3-FZYqdaqoiZk.mp4 13.6 MBPart 01-Module 04-Lesson 06_Alpha Factors/34. M4 L3a 151 The Fundamental Law Of Active Management Part 1 V4-iCW_vqvrTlw.mp4 13.6 MBPart 06-Module 01-Lesson 06_Conditional Probability/13. Two Coins 3-JIWv5fU3GLA.mp4 13.5 MBPart 02-Module 02-Lesson 03_Deep Learning with PyTorch/16. PyTorch V2 Part 5 V1 (1)-XACXlkIdS7Y.mp4 13.4 MBPart 03-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.mp4 13.4 MBPart 02-Module 03-Lesson 07_Feature Importance/11. M7L7 51 Shap One Solution V2 (1)-Q0qAsUz2gnU.mp4 13.4 MBPart 07-Module 01-Lesson 03_Clustering/02. Unsupervised Learning-Mx9f99bRB3Q.mp4 13.3 MBPart 02-Module 01-Lesson 05_Financial Statements/16. AIT M5L4B 06 Introduction To Beautifulsoup V3-k8e-kB3qBng.mp4 13.3 MBPart 01-Module 04-Lesson 02_Factor Models and Types of Factors/16. M4 L1B 15 Volume Factors V1-1dTAV3Irxv4.mp4 13.2 MBPart 02-Module 03-Lesson 02_Decision Trees/09. Entropy-piLpj1V1HEk.mp4 13.2 MBPart 07-Module 01-Lesson 04_Decision Trees/07. Entropy-piLpj1V1HEk.mp4 13.2 MBPart 06-Module 01-Lesson 09_Normal Distribution Theory/13. Formula Summary-zqo1RJEHT_0.mp4 13.2 MBPart 06-Module 01-Lesson 07_Bayes Rule/08. Bayes Rule Diagram-b8M9CWxRyQ4.mp4 13.1 MBPart 01-Module 02-Lesson 05_Volatility/11. M2L5 11 Markets Volatility V3-jEHJkZUX9s4.mp4 13.1 MBPart 02-Module 03-Lesson 05_Feature Engineering/11. M7L5 28 V1-Ffax3lTKAs0.mp4 13.1 MBPart 02-Module 02-Lesson 04_Recurrent Neural Networks/21. 08 Making Predictions V3-BhrpV3kwATo.mp4 13.0 MBPart 02-Module 03-Lesson 02_Decision Trees/11. MLND SL DT 08 Entropy Formula 2 MAIN V2-6GHg70hrSJw.mp4 12.9 MBPart 07-Module 01-Lesson 04_Decision Trees/09. MLND SL DT 08 Entropy Formula 2 MAIN V2-6GHg70hrSJw.mp4 12.9 MBPart 02-Module 02-Lesson 03_Deep Learning with PyTorch/04. PyTorch V2 Part 1 V1-6Z7WntXays8.mp4 12.9 MBPart 01-Module 03-Lesson 02_ETFs/09. L2 11 2 Arbitrage Farmers Market V1-hHxp16mQNGA.mp4 12.8 MBPart 01-Module 04-Lesson 02_Factor Models and Types of Factors/22. M4 L1B 21 Analyst Ratings V1-cHkJo8qBKes.mp4 12.8 MBPart 06-Module 01-Lesson 12_Hypothesis Testing/27. What If Our Sample Is Large-WoTCeSTL1eM.mp4 12.5 MBPart 06-Module 01-Lesson 05_Binomial Distribution/06. 5 Flips 3 Heads-pOKmt4w8T3g.mp4 12.5 MBPart 02-Module 01-Lesson 05_Financial Statements/21. M5 SC 12 Searching The Parse Tree Part 1 V1-RyJuvYTF3Ms.mp4 12.5 MBPart 02-Module 01-Lesson 05_Financial Statements/07. M5 SC 2 Finding Words V1-wTOh9B6aHGk.mp4 12.3 MBPart 01-Module 04-Lesson 06_Alpha Factors/24. M4 L3a 12 Return Denominator Leverage And Factor Returns V3-QxHrP5LoXAI.mp4 12.3 MBPart 01-Module 04-Lesson 08_Advanced Portfolio Optimization/14. M4 L4 17 Path Dependency 1 V3-ok9rKYRtZLE.mp4 12.2 MBPart 06-Module 01-Lesson 06_Conditional Probability/10. Total Probability-YSYpzFR4k1I.mp4 12.1 MBPart 01-Module 04-Lesson 02_Factor Models and Types of Factors/15. M4 L1B 14 PriceVolume Factors V2-zaG0PDc3wsA.mp4 12.1 MBPart 06-Module 01-Lesson 12_Hypothesis Testing/09. Types Of Errors - Part II-mbdSQ5CjdFs.mp4 12.0 MBPart 02-Module 05-Lesson 01_Intro to Backtesting/07. M8L1 14 Structural Changes V1-EaxepBSycbQ.mp4 12.0 MBPart 06-Module 01-Lesson 07_Bayes Rule/21. Robot Sensing 1-_DjfTytro6I.mp4 12.0 MBPart 03-Module 01-Lesson 05_Scripting/20. Importing Files-qjeSn6zZbR0.mp4 12.0 MBPart 02-Module 02-Lesson 05_Embeddings Word2Vec/10. 8 Word2vec Model V2-7BEYWhym8lI.mp4 11.9 MBPart 06-Module 01-Lesson 04_Probability/02. Flipping Coins-OpNufHYgJCg.mp4 11.9 MBPart 01-Module 04-Lesson 06_Alpha Factors/30. M4 L3A 141 Ranked Information Coefficient Part 1 V4-_huNulOIuB0.mp4 11.9 MBPart 02-Module 01-Lesson 05_Financial Statements/05. AIT M5L4B 01 Introduction To Regex V4-WCXDD_n1ZuA.mp4 11.8 MBPart 01-Module 02-Lesson 03_Regression/06. Testing For Normalilty-Sa1MJegyYfc.mp4 11.8 MBPart 06-Module 01-Lesson 04_Probability/18. Doubles-fkUyTJNbdzU.mp4 11.8 MBPart 01-Module 03-Lesson 03_Portfolio Risk and Return/11. L3 09 Capital Market Line V2-BRO-vo3y0-U.mp4 11.8 MBPart 06-Module 01-Lesson 04_Probability/16. One Of Three 2-27Ed1GI4j84.mp4 11.8 MBPart 09-Module 01-Lesson 01_Intro to Computer Vision/04. 04. Computer Vision Applications-aFJKp2NltCY.mp4 11.7 MBPart 06-Module 01-Lesson 09_Normal Distribution Theory/02. Shape-DjsL64Kjr1Q.mp4 11.7 MBPart 01-Module 04-Lesson 07_Alpha Factor Research Methods/12. M4 L3b 09 Winners And Losers Creating A Joint Factor V3-xmW05ii8Vxs.mp4 11.7 MBPart 01-Module 04-Lesson 07_Alpha Factor Research Methods/22. M4 L3b 18 IVol Value Fundamental Or Discretionary Investing V2-sKAE5Z8e7IM.mp4 11.7 MBPart 02-Module 01-Lesson 06_Basic NLP Analysis/07. AIT M5L5 08 Similarity Analysis V3-LNro_9JOIrY.mp4 11.7 MBPart 01-Module 02-Lesson 04_Time Series Modeling/06. 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