Time Series Analysis, Forecasting, and Machine Learning

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Time Series Analysis, Forecasting, and Machine Learning

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Time Series Analysis, Forecasting, and Machine Learning
01 Welcome
001 Introduction and Outline.en.srt
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7.78 KB
001 Introduction and Outline.mp4
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30.69 MB
002 Where to Get the Code.en.srt
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16.03 KB
002 Where to Get the Code.mp4
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61.97 MB
003 Warmup (Optional).en.srt
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003 Warmup (Optional).mp4
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23.16 MB
external-assets-links.txt
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80 B
02 Time Series Basics
001 Time Series Basics Section Introduction.en.srt
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001 Time Series Basics Section Introduction.mp4
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17.46 MB
002 What is a Time Series_.en.srt
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002 What is a Time Series_.mp4
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003 Modeling vs. Predicting.en.srt
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003 Modeling vs. Predicting.mp4
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004 Why Do We Care About Shapes_.en.srt
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004 Why Do We Care About Shapes_.mp4
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005 Types of Tasks.en.srt
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005 Types of Tasks.mp4
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006 Power, Log, and Box-Cox Transformations.en.srt
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006 Power, Log, and Box-Cox Transformations.mp4
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007 Power, Log, and Box-Cox Transformations in Code.en.srt
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007 Power, Log, and Box-Cox Transformations in Code.mp4
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008 Forecasting Metrics.en.srt
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008 Forecasting Metrics.mp4
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009 Financial Time Series Primer.en.srt
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009 Financial Time Series Primer.mp4
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010 Price Simulations in Code.en.srt
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010 Price Simulations in Code.mp4
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011 Random Walks and the Random Walk Hypothesis.en.srt
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011 Random Walks and the Random Walk Hypothesis.mp4
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012 The Naive Forecast and the Importance of Baselines.en.srt
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012 The Naive Forecast and the Importance of Baselines.mp4
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013 Naive Forecast and Forecasting Metrics in Code.en.srt
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013 Naive Forecast and Forecasting Metrics in Code.mp4
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014 Time Series Basics Section Summary.en.srt
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014 Time Series Basics Section Summary.mp4
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015 Suggestion Box.en.srt
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015 Suggestion Box.mp4
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03 Exponential Smoothing and ETS Methods
001 Exponential Smoothing Section Introduction.en.srt
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001 Exponential Smoothing Section Introduction.mp4
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13.56 MB
002 Exponential Smoothing Intuition for Beginners.en.srt
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002 Exponential Smoothing Intuition for Beginners.mp4
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003 SMA Theory.en.srt
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003 SMA Theory.mp4
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004 SMA Code.en.srt
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004 SMA Code.mp4
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005 EWMA Theory.en.srt
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005 EWMA Theory.mp4
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006 EWMA Code.en.srt
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006 EWMA Code.mp4
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007 SES Theory.en.srt
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007 SES Theory.mp4
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008 SES Code.en.srt
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008 SES Code.mp4
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009 Holt's Linear Trend Model (Theory).en.srt
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009 Holt's Linear Trend Model (Theory).mp4
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010 Holt's Linear Trend Model (Code).en.srt
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010 Holt's Linear Trend Model (Code).mp4
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011 Holt-Winters (Theory).en.srt
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011 Holt-Winters (Theory).mp4
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012 Holt-Winters (Code).en.srt
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012 Holt-Winters (Code).mp4
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013 Walk-Forward Validation.en.srt
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013 Walk-Forward Validation.mp4
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014 Walk-Forward Validation in Code.en.srt
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014 Walk-Forward Validation in Code.mp4
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015 Application_ Sales Data.en.srt
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015 Application_ Sales Data.mp4
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016 Application_ Stock Predictions.en.srt
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016 Application_ Stock Predictions.mp4
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017 SMA Application_ COVID-19 Counting.en.srt
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017 SMA Application_ COVID-19 Counting.mp4
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018 SMA Application_ Algorithmic Trading.en.srt
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018 SMA Application_ Algorithmic Trading.mp4
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019 Exponential Smoothing Section Summary.en.srt
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019 Exponential Smoothing Section Summary.mp4
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04 ARIMA
001 ARIMA Section Introduction.en.srt
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001 ARIMA Section Introduction.mp4
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002 Autoregressive Models - AR(p).en.srt
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002 Autoregressive Models - AR(p).mp4
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003 Moving Average Models - MA(q).en.srt
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003 Moving Average Models - MA(q).mp4
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004 ARIMA.en.srt
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004 ARIMA.mp4
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005 ARIMA in Code.en.srt
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005 ARIMA in Code.mp4
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006 Stationarity.en.srt
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006 Stationarity.mp4
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007 Stationarity in Code.en.srt
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007 Stationarity in Code.mp4
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008 ACF (Autocorrelation Function).en.srt
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008 ACF (Autocorrelation Function).mp4
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009 PACF (Partial Autocorrelation Funtion).en.srt
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009 PACF (Partial Autocorrelation Funtion).mp4
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010 ACF and PACF in Code (pt 1).en.srt
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010 ACF and PACF in Code (pt 1).mp4
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011 ACF and PACF in Code (pt 2).en.srt
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011 ACF and PACF in Code (pt 2).mp4
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012 Auto ARIMA and SARIMAX.en.srt
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012 Auto ARIMA and SARIMAX.mp4
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013 Model Selection, AIC and BIC.en.srt
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013 Model Selection, AIC and BIC.mp4
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014 Auto ARIMA in Code.en.srt
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014 Auto ARIMA in Code.mp4
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015 Auto ARIMA in Code (Stocks).en.srt
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015 Auto ARIMA in Code (Stocks).mp4
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016 ACF and PACF for Stock Returns.en.srt
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016 ACF and PACF for Stock Returns.mp4
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017 Auto ARIMA in Code (Sales Data).en.srt
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017 Auto ARIMA in Code (Sales Data).mp4
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018 How to Forecast with ARIMA.en.srt
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018 How to Forecast with ARIMA.mp4
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019 ARIMA Section Summary.en.srt
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019 ARIMA Section Summary.mp4
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GetFreeCourses.Co.url
URL
116 B
05 Machine Learning Methods
001 Machine Learning Section Introduction.en.srt
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001 Machine Learning Section Introduction.mp4
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002 Supervised Machine Learning_ Classification and Regression.en.srt
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002 Supervised Machine Learning_ Classification and Regression.mp4
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68.96 MB
003 Autoregressive Machine Learning Models.en.srt
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003 Autoregressive Machine Learning Models.mp4
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004 Machine Learning Algorithms_ Linear Regression.en.srt
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004 Machine Learning Algorithms_ Linear Regression.mp4
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005 Machine Learning Algorithms_ Logistic Regression.en.srt
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005 Machine Learning Algorithms_ Logistic Regression.mp4
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006 Machine Learning Algorithms_ Support Vector Machines.en.srt
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006 Machine Learning Algorithms_ Support Vector Machines.mp4
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007 Machine Learning Algorithms_ Random Forest.en.srt
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007 Machine Learning Algorithms_ Random Forest.mp4
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008 Extrapolation and Stock Prices.en.srt
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008 Extrapolation and Stock Prices.mp4
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009 Machine Learning for Time Series Forecasting in Code (pt 1).en.srt
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009 Machine Learning for Time Series Forecasting in Code (pt 1).mp4
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010 Forecasting with Differencing.en.srt
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010 Forecasting with Differencing.mp4
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011 Machine Learning for Time Series Forecasting in Code (pt 2).en.srt
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011 Machine Learning for Time Series Forecasting in Code (pt 2).mp4
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012 Application_ Sales Data.en.srt
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012 Application_ Sales Data.mp4
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013 Application_ Predicting Stock Prices and Returns.en.srt
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013 Application_ Predicting Stock Prices and Returns.mp4
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014 Application_ Predicting Stock Movements.en.srt
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014 Application_ Predicting Stock Movements.mp4
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015 Machine Learning Section Summary.en.srt
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015 Machine Learning Section Summary.mp4
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06 Deep Learning_ Artificial Neural Networks (ANN)
001 Artificial Neural Networks_ Section Introduction.en.srt
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001 Artificial Neural Networks_ Section Introduction.mp4
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002 The Neuron.en.srt
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002 The Neuron.mp4
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003 Forward Propagation.en.srt
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003 Forward Propagation.mp4
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004 The Geometrical Picture.en.srt
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004 The Geometrical Picture.mp4
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005 Activation Functions.en.srt
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005 Activation Functions.mp4
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006 Multiclass Classification.en.srt
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006 Multiclass Classification.mp4
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007 ANN Code Preparation.en.srt
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007 ANN Code Preparation.mp4
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008 Feedforward ANN for Time Series Forecasting Code.en.srt
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008 Feedforward ANN for Time Series Forecasting Code.mp4
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009 Feedforward ANN for Stock Return and Price Predictions Code.en.srt
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009 Feedforward ANN for Stock Return and Price Predictions Code.mp4
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010 Human Activity Recognition Dataset.en.srt
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010 Human Activity Recognition Dataset.mp4
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011 Human Activity Recognition_ Code Preparation.en.srt
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011 Human Activity Recognition_ Code Preparation.mp4
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012 Human Activity Recognition_ Data Exploration.en.srt
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012 Human Activity Recognition_ Data Exploration.mp4
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013 Human Activity Recognition_ Multi-Input ANN.en.srt
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013 Human Activity Recognition_ Multi-Input ANN.mp4
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014 Human Activity Recognition_ Feature-Based Model.en.srt
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014 Human Activity Recognition_ Feature-Based Model.mp4
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015 Human Activity Recognition_ Combined Model.en.srt
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015 Human Activity Recognition_ Combined Model.mp4
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016 How Does a Neural Network _Learn__.en.srt
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016 How Does a Neural Network _Learn__.mp4
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017 Artificial Neural Networks_ Section Summary.en.srt
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017 Artificial Neural Networks_ Section Summary.mp4
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07 Deep Learning_ Convolutional Neural Networks (CNN)
001 CNN Section Introduction.en.srt
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001 CNN Section Introduction.mp4
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002 What is Convolution_.en.srt
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002 What is Convolution_.mp4
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003 What is Convolution_ (Pattern-Matching).en.srt
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003 What is Convolution_ (Pattern-Matching).mp4
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004 What is Convolution_ (Weight Sharing).en.srt
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004 What is Convolution_ (Weight Sharing).mp4
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005 Convolution on Color Images.en.srt
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005 Convolution on Color Images.mp4
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006 Convolution for Time Series and ARIMA.en.srt
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006 Convolution for Time Series and ARIMA.mp4
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007 CNN Architecture.en.srt
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007 CNN Architecture.mp4
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008 CNN Code Preparation.en.srt
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008 CNN Code Preparation.mp4
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009 CNN for Time Series Forecasting in Code.en.srt
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009 CNN for Time Series Forecasting in Code.mp4
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010 CNN for Human Activity Recognition.en.srt
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010 CNN for Human Activity Recognition.mp4
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011 CNN Section Summary.en.srt
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011 CNN Section Summary.mp4
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08 VIP_ AWS Forecast
001 AWS Forecast Section Introduction.en.srt
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001 AWS Forecast Section Introduction.mp4
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002 Data Model.en.srt
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002 Data Model.mp4
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003 Creating an IAM Role.en.srt
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003 Creating an IAM Role.mp4
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004 Code pt 1 (Getting and Transforming the Data).en.srt
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004 Code pt 1 (Getting and Transforming the Data).mp4
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005 Code pt 2 (Uploading the data to S3).en.srt
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005 Code pt 2 (Uploading the data to S3).mp4
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006 Code pt 3 (Building your Model).en.srt
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006 Code pt 3 (Building your Model).mp4
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007 Code pt 4 (Generating and Evaluating the Forecast).en.srt
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007 Code pt 4 (Generating and Evaluating the Forecast).mp4
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008 AWS Forecast Exercise.en.srt
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008 AWS Forecast Exercise.mp4
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009 AWS Forecast Section Summary.en.srt
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009 AWS Forecast Section Summary.mp4
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09 Extras
001 Colab Notebooks.html
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10 Setting Up Your Environment FAQ
001 Anaconda Environment Setup.en.srt
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001 Anaconda Environment Setup.mp4
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002 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.en.srt
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002 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
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11 Extra Help With Python Coding for Beginners FAQ
001 How to Code by Yourself (part 1).en.srt
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001 How to Code by Yourself (part 1).mp4
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002 How to Code by Yourself (part 2).en.srt
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002 How to Code by Yourself (part 2).mp4
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003 Proof that using Jupyter Notebook is the same as not using it.en.srt
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003 Proof that using Jupyter Notebook is the same as not using it.mp4
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GetFreeCourses.Co.url
URL
116 B
12 Effective Learning Strategies for Machine Learning FAQ
001 How to Succeed in this Course (Long Version).en.srt
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001 How to Succeed in this Course (Long Version).mp4
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002 Is this for Beginners or Experts_ Academic or Practical_ Fast or slow-paced_.en.srt
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002 Is this for Beginners or Experts_ Academic or Practical_ Fast or slow-paced_.mp4
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003 Machine Learning and AI Prerequisite Roadmap (pt 1).en.srt
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003 Machine Learning and AI Prerequisite Roadmap (pt 1).mp4
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004 Machine Learning and AI Prerequisite Roadmap (pt 2).en.srt
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004 Machine Learning and AI Prerequisite Roadmap (pt 2).mp4
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13 Appendix _ FAQ Finale
001 What is the Appendix_.en.srt
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001 What is the Appendix_.mp4
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002 BONUS_ Where to get discount coupons and FREE deep learning material.en.srt
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002 BONUS_ Where to get discount coupons and FREE deep learning material.mp4
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Download Paid Udemy Courses For Free.url
URL
116 B
GetFreeCourses.Co.url
URL
116 B

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