Udemy - Complete Python and Machine Learning in Financial Analysis (3.2025)

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Udemy - Complete Python and Machine Learning in Financial Analysis (3.2025)

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种子哈希：be73434f3af505c5ec3b07ebdee885f0525e7d46
文件大小： 5.94G
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收录时间：2025-08-11
最近下载：2025-08-11

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文件列表

  • 10 - Deep Learning in Finance/3 -Multilayer perceptrons for time series forecasting.mp4 284.7 MB
  • 9 - Advanced Machine Learning Models in Finance/7 -Bayesian hyperparameter optimization.mp4 276.5 MB
  • 10 - Deep Learning in Finance/4 -Convolutional neural networks for time series forecasting.mp4 259.7 MB
  • 9 - Advanced Machine Learning Models in Finance/3 -Theres more about use advanced classifiers to achieve better results.mp4 236.4 MB
  • 9 - Advanced Machine Learning Models in Finance/5 -Investigating the feature importance.mp4 207.0 MB
  • 6 - Monte Carlo Simulations in Finance/2 -Simulating stock price dynamics using Geometric Brownian Motion.mp4 206.7 MB
  • 10 - Deep Learning in Finance/5 -Recurrent neural networks for time series forecasting.mp4 200.2 MB
  • 3 - Time Series Modeling/6 -Modeling time series with ARIMA class models.mp4 182.7 MB
  • 10 - Deep Learning in Finance/2 -Deep learning for tabular data.mp4 173.3 MB
  • 2 - Technical Analysis in Python/3 -Backtesting a strategy based on simple moving average.mp4 171.5 MB
  • 8 - Identifying Credit Default with Machine Learning/3 -Exploratory data analysis.mp4 169.4 MB
  • 1 - Financial Data and Preprocessing/10 -Investigating stylized facts of asset returns.mp4 165.6 MB
  • 2 - Technical Analysis in Python/4 -Calculating Bollinger Bands and testing a buysell strategy.mp4 161.2 MB
  • 2 - Technical Analysis in Python/6 -Building an interactive dashboard for TA.mp4 158.8 MB
  • 8 - Identifying Credit Default with Machine Learning/9 -Tuning hyperparameters using grid search and cross-validation.mp4 127.4 MB
  • 9 - Advanced Machine Learning Models in Finance/2 -Investigating advanced classifiers.mp4 122.6 MB
  • 8 - Identifying Credit Default with Machine Learning/7 -Fitting a decision tree classifier.mp4 115.8 MB
  • 8 - Identifying Credit Default with Machine Learning/5 -Dealing with missing values.mp4 115.0 MB
  • 3 - Time Series Modeling/5 -Modeling time series with exponential smoothing methods.mp4 112.6 MB
  • 4 - Multi-Factor Models/5 -Implementing the four- and five-factor models in Python.mp4 111.8 MB
  • 9 - Advanced Machine Learning Models in Finance/6 -Investigating different approaches to handling imbalanced data.mp4 111.7 MB
  • 7 - Asset Allocation in Python/4 -Finding the Efficient Frontier using optimization with scipy.mp4 111.6 MB
  • 7 - Asset Allocation in Python/3 -Finding the Efficient Frontier using Monte Carlo simulations.mp4 105.0 MB
  • 3 - Time Series Modeling/4 -Correcting for stationarity in time series.mp4 104.8 MB
  • 5 - Modeling Volatility with GARCH Class Models/4 -Implementing a CCC-GARCH model for multivariate volatility forecasting.mp4 100.4 MB
  • 4 - Multi-Factor Models/4 -Implementing the rolling three-factor model on a portfolio of assets.mp4 99.0 MB
  • 3 - Time Series Modeling/3 -Testing for stationarity in time series.mp4 96.2 MB
  • 6 - Monte Carlo Simulations in Finance/4 -Pricing American options with Least Squares Monte Carlo.mp4 94.8 MB
  • 4 - Multi-Factor Models/3 -Implementing the Fama-French three-factor model in Python.mp4 87.9 MB
  • 8 - Identifying Credit Default with Machine Learning/8 -Implementing scikit-learn's pipelines.mp4 86.9 MB
  • 6 - Monte Carlo Simulations in Finance/6 -Estimating value-at-risk using Monte Carlo.mp4 85.7 MB
  • 9 - Advanced Machine Learning Models in Finance/4 -Using stacking for improved performance.mp4 84.3 MB
  • 6 - Monte Carlo Simulations in Finance/5 -Pricing American options using Quantlib.mp4 83.6 MB
  • 8 - Identifying Credit Default with Machine Learning/2 -Loading data and managing data types.mp4 83.4 MB
  • 1 - Financial Data and Preprocessing/8 -Visualizing time series data.mp4 78.0 MB
  • 2 - Technical Analysis in Python/5 -Calculating the relative strength index and testing a longshort strategy.mp4 77.1 MB
  • 5 - Modeling Volatility with GARCH Class Models/5 -Forecasting a conditional covariance matrix using DCC-GARCH.mp4 75.6 MB
  • 10 - Deep Learning in Finance/1 -Introduction.mp4 74.1 MB
  • 1 - Financial Data and Preprocessing/1 -Introduction of Python Programming in Financial Analysis.mp4 72.6 MB
  • 5 - Modeling Volatility with GARCH Class Models/2 -Explaining stock returns' volatility with ARCH models.mp4 71.9 MB
  • 8 - Identifying Credit Default with Machine Learning/6 -Encoding categorical variables.mp4 70.5 MB
  • 6 - Monte Carlo Simulations in Finance/3 -Pricing European options using simulations.mp4 69.1 MB
  • 7 - Asset Allocation in Python/2 -Evaluating the performance of a basic 1n portfolio.mp4 68.8 MB
  • 3 - Time Series Modeling/2 -Decomposing time series.mp4 58.8 MB
  • 1 - Financial Data and Preprocessing/6 -Converting prices to returns.mp4 58.4 MB
  • 4 - Multi-Factor Models/2 -Implementing the CAPM in Python.mp4 58.4 MB
  • 1 - Financial Data and Preprocessing/9 -Identifying outliers.mp4 57.7 MB
  • 3 - Time Series Modeling/7 -Forecasting using ARIMA class models.mp4 57.2 MB
  • 7 - Asset Allocation in Python/1 -Introduction.mp4 43.0 MB
  • 1 - Financial Data and Preprocessing/7 -Changing frequency.mp4 42.1 MB
  • 9 - Advanced Machine Learning Models in Finance/1 -Introduction.mp4 38.1 MB
  • 8 - Identifying Credit Default with Machine Learning/4 -Splitting data into training and test sets.mp4 36.6 MB
  • 8 - Identifying Credit Default with Machine Learning/1 -Introduction.mp4 36.0 MB
  • 1 - Financial Data and Preprocessing/2 -Introduction of Financial Analysis.mp4 33.5 MB
  • 5 - Modeling Volatility with GARCH Class Models/3 -Explaining stock returns' volatility with GARCH models.mp4 31.7 MB
  • 1 - Financial Data and Preprocessing/4 -Getting data from Yahoo Finance.mp4 29.9 MB
  • 1 - Financial Data and Preprocessing/5 -Getting data from Quandl.mp4 28.1 MB
  • 6 - Monte Carlo Simulations in Finance/1 -Introduction.mp4 27.6 MB
  • 5 - Modeling Volatility with GARCH Class Models/1 -Introduction.mp4 27.5 MB
  • 2 - Technical Analysis in Python/2 -Creating a candlestick chart.mp4 27.2 MB
  • 1 - Financial Data and Preprocessing/3 -Introduction.mp4 15.7 MB
  • 2 - Technical Analysis in Python/1 -Introduction.mp4 14.9 MB
  • 9 - Advanced Machine Learning Models in Finance/8 -Chapter_9.zip 13.5 MB
  • 7 - Asset Allocation in Python/5 -Chapter_7.zip 12.3 MB
  • 8 - Identifying Credit Default with Machine Learning/10 -Chapter_8.zip 11.7 MB
  • 2 - Technical Analysis in Python/7 -Chapter_2.zip 8.8 MB
  • 3 - Time Series Modeling/8 -Chapter_3.zip 8.7 MB
  • 10 - Deep Learning in Finance/2 -requirements_of_chapter_10.zip 7.4 MB
  • 4 - Multi-Factor Models/1 -Introduction.mp4 6.9 MB
  • 1 - Financial Data and Preprocessing/11 -Chapter 1.zip 6.5 MB
  • 3 - Time Series Modeling/1 -Introduction.mp4 6.5 MB
  • 9 - Advanced Machine Learning Models in Finance/2 -requirements_of_chapter_9.zip 5.2 MB
  • 6 - Monte Carlo Simulations in Finance/7 -Chapter_6.zip 5.1 MB
  • 8 - Identifying Credit Default with Machine Learning/2 -requirements_of_chapter_8.zip 5.0 MB
  • 10 - Deep Learning in Finance/6 -Chapter_10.zip 3.3 MB
  • 5 - Modeling Volatility with GARCH Class Models/6 -Chapter_5.zip 2.8 MB
  • 4 - Multi-Factor Models/6 -Chapter_4.zip 1.7 MB
  • 2 - Technical Analysis in Python/2 -requirements_of_chapter_2.zip 517.5 kB
  • 5 - Modeling Volatility with GARCH Class Models/2 -requirements_of_chapter_5.zip 59.0 kB
  • 4 - Multi-Factor Models/2 -requirements_of_chapter_4.zip 53.8 kB
  • 10 - Deep Learning in Finance/3 -Multilayer perceptrons for time series forecasting.vtt 21.9 kB
  • 9 - Advanced Machine Learning Models in Finance/7 -Bayesian hyperparameter optimization.vtt 15.4 kB
  • 10 - Deep Learning in Finance/4 -Convolutional neural networks for time series forecasting.vtt 15.2 kB
  • 10 - Deep Learning in Finance/2 -Deep learning for tabular data.vtt 13.8 kB
  • 10 - Deep Learning in Finance/5 -Recurrent neural networks for time series forecasting.vtt 12.9 kB
  • 1 - Financial Data and Preprocessing/10 -Investigating stylized facts of asset returns.vtt 12.8 kB
  • 8 - Identifying Credit Default with Machine Learning/3 -Exploratory data analysis.vtt 12.4 kB
  • 3 - Time Series Modeling/6 -Modeling time series with ARIMA class models.vtt 12.1 kB
  • 8 - Identifying Credit Default with Machine Learning/9 -Tuning hyperparameters using grid search and cross-validation.vtt 12.1 kB
  • 2 - Technical Analysis in Python/3 -Backtesting a strategy based on simple moving average.vtt 10.3 kB
  • 8 - Identifying Credit Default with Machine Learning/7 -Fitting a decision tree classifier.vtt 10.3 kB
  • 9 - Advanced Machine Learning Models in Finance/5 -Investigating the feature importance.vtt 10.2 kB
  • 6 - Monte Carlo Simulations in Finance/2 -Simulating stock price dynamics using Geometric Brownian Motion.vtt 9.7 kB
  • 7 - Asset Allocation in Python/4 -Finding the Efficient Frontier using optimization with scipy.vtt 9.1 kB
  • 1 - Financial Data and Preprocessing/1 -Introduction of Python Programming in Financial Analysis.vtt 8.9 kB
  • 3 - Time Series Modeling/5 -Modeling time series with exponential smoothing methods.vtt 8.3 kB
  • 9 - Advanced Machine Learning Models in Finance/6 -Investigating different approaches to handling imbalanced data.vtt 8.3 kB
  • 8 - Identifying Credit Default with Machine Learning/6 -Encoding categorical variables.vtt 8.1 kB
  • 6 - Monte Carlo Simulations in Finance/4 -Pricing American options with Least Squares Monte Carlo.vtt 7.9 kB
  • 8 - Identifying Credit Default with Machine Learning/2 -Loading data and managing data types.vtt 7.7 kB
  • 7 - Asset Allocation in Python/3 -Finding the Efficient Frontier using Monte Carlo simulations.vtt 6.8 kB
  • 5 - Modeling Volatility with GARCH Class Models/5 -Forecasting a conditional covariance matrix using DCC-GARCH.vtt 6.7 kB
  • 6 - Monte Carlo Simulations in Finance/6 -Estimating value-at-risk using Monte Carlo.vtt 6.6 kB
  • 8 - Identifying Credit Default with Machine Learning/5 -Dealing with missing values.vtt 6.6 kB
  • 8 - Identifying Credit Default with Machine Learning/8 -Implementing scikit-learn's pipelines.vtt 6.1 kB
  • 10 - Deep Learning in Finance/1 -Introduction.vtt 6.0 kB
  • 6 - Monte Carlo Simulations in Finance/5 -Pricing American options using Quantlib.vtt 6.0 kB
  • 1 - Financial Data and Preprocessing/6 -Converting prices to returns.vtt 5.8 kB
  • 4 - Multi-Factor Models/5 -Implementing the four- and five-factor models in Python.vtt 5.8 kB
  • 2 - Technical Analysis in Python/4 -Calculating Bollinger Bands and testing a buysell strategy.vtt 5.7 kB
  • 3 - Time Series Modeling/4 -Correcting for stationarity in time series.vtt 5.5 kB
  • 4 - Multi-Factor Models/3 -Implementing the Fama-French three-factor model in Python.vtt 5.4 kB
  • 9 - Advanced Machine Learning Models in Finance/4 -Using stacking for improved performance.vtt 5.3 kB
  • 2 - Technical Analysis in Python/6 -Building an interactive dashboard for TA.vtt 5.3 kB
  • 2 - Technical Analysis in Python/5 -Calculating the relative strength index and testing a longshort strategy.vtt 5.3 kB
  • 3 - Time Series Modeling/2 -Decomposing time series.vtt 5.3 kB
  • 7 - Asset Allocation in Python/2 -Evaluating the performance of a basic 1n portfolio.vtt 5.2 kB
  • 1 - Financial Data and Preprocessing/8 -Visualizing time series data.vtt 5.2 kB
  • 6 - Monte Carlo Simulations in Finance/2 -requirements_of_chapter_6.zip 5.0 kB
  • 6 - Monte Carlo Simulations in Finance/3 -Pricing European options using simulations.vtt 4.9 kB
  • 5 - Modeling Volatility with GARCH Class Models/2 -Explaining stock returns' volatility with ARCH models.vtt 4.7 kB
  • 8 - Identifying Credit Default with Machine Learning/4 -Splitting data into training and test sets.vtt 4.7 kB
  • 9 - Advanced Machine Learning Models in Finance/2 -Investigating advanced classifiers.vtt 4.5 kB
  • 5 - Modeling Volatility with GARCH Class Models/4 -Implementing a CCC-GARCH model for multivariate volatility forecasting.vtt 4.5 kB
  • 4 - Multi-Factor Models/2 -Implementing the CAPM in Python.vtt 4.5 kB
  • 4 - Multi-Factor Models/4 -Implementing the rolling three-factor model on a portfolio of assets.vtt 4.5 kB
  • 3 - Time Series Modeling/3 -Testing for stationarity in time series.vtt 4.2 kB
  • 7 - Asset Allocation in Python/1 -Introduction.vtt 4.2 kB
  • 5 - Modeling Volatility with GARCH Class Models/3 -Explaining stock returns' volatility with GARCH models.vtt 4.0 kB
  • 1 - Financial Data and Preprocessing/9 -Identifying outliers.vtt 4.0 kB
  • 8 - Identifying Credit Default with Machine Learning/1 -Introduction.vtt 3.7 kB
  • 3 - Time Series Modeling/2 -requirements_of_chapter_3.zip 3.7 kB
  • 1 - Financial Data and Preprocessing/2 -Introduction of Financial Analysis.vtt 3.7 kB
  • 5 - Modeling Volatility with GARCH Class Models/1 -Introduction.vtt 3.6 kB
  • 1 - Financial Data and Preprocessing/4 -Getting data from Yahoo Finance.vtt 3.5 kB
  • 3 - Time Series Modeling/7 -Forecasting using ARIMA class models.vtt 3.2 kB
  • 9 - Advanced Machine Learning Models in Finance/1 -Introduction.vtt 3.2 kB
  • 6 - Monte Carlo Simulations in Finance/1 -Introduction.vtt 3.0 kB
  • 1 - Financial Data and Preprocessing/7 -Changing frequency.vtt 2.8 kB
  • 2 - Technical Analysis in Python/1 -Introduction.vtt 2.7 kB
  • 2 - Technical Analysis in Python/2 -Creating a candlestick chart.vtt 2.5 kB
  • 1 - Financial Data and Preprocessing/3 -Introduction.vtt 2.3 kB
  • 1 - Financial Data and Preprocessing/5 -Getting data from Quandl.vtt 1.9 kB
  • 4 - Multi-Factor Models/1 -Introduction.vtt 1.5 kB
  • 3 - Time Series Modeling/1 -Introduction.vtt 1.3 kB
  • 9 - Advanced Machine Learning Models in Finance/3 -Theres more about use advanced classifiers to achieve better results.vtt 811 Bytes
  • 10 - Deep Learning in Finance/6 - The End.html 48 Bytes
  • 10 - Deep Learning in Finance/2 - requirements of chapter 10.html 42 Bytes
  • 2 - Technical Analysis in Python/2 - requirements of chapter 2.html 41 Bytes
  • 3 - Time Series Modeling/2 - requirements of chapter 3.html 41 Bytes
  • 4 - Multi-Factor Models/2 - requirements of chapter 4.html 41 Bytes
  • 5 - Modeling Volatility with GARCH Class Models/2 - requirements of chapter 5.html 41 Bytes
  • 6 - Monte Carlo Simulations in Finance/2 - requirements of chapter 6.html 41 Bytes
  • 8 - Identifying Credit Default with Machine Learning/2 - requirements of chapter 8.html 41 Bytes
  • 9 - Advanced Machine Learning Models in Finance/2 - requirements of chapter 9.html 41 Bytes
  • 10 - Deep Learning in Finance/6 - Codes of Chapter 10.html 39 Bytes
  • 1 - Financial Data and Preprocessing/11 - Codes of Chapter 1.html 38 Bytes
  • 2 - Technical Analysis in Python/7 - Codes of Chapter 2.html 38 Bytes
  • 3 - Time Series Modeling/8 - Codes of Chapter 3.html 38 Bytes
  • 4 - Multi-Factor Models/6 - Codes of Chapter 4.html 38 Bytes
  • 5 - Modeling Volatility with GARCH Class Models/6 - Codes of Chapter 5.html 38 Bytes
  • 6 - Monte Carlo Simulations in Finance/7 - Codes of Chapter 6.html 38 Bytes
  • 7 - Asset Allocation in Python/5 - Codes of Chapter 7.html 38 Bytes
  • 8 - Identifying Credit Default with Machine Learning/10 - Codes of Chapter 8.html 38 Bytes
  • 9 - Advanced Machine Learning Models in Finance/8 - Codes of Chapter 9.html 38 Bytes

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