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~Get Your Files Here !/3. Preparing the Data/012. Write out all train, validation, and test sets.mp4 47.9 MB
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~Get Your Files Here !/4. What is Ensemble Learning/013. What is ensemble learning.mp4 37.9 MB
~Get Your Files Here !/7. Stacking/032. Explore stacking algorithms in Python.mp4 37.6 MB
~Get Your Files Here !/6. Bagging/025. What are examples of algorithms that use bagging.mp4 37.6 MB
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04 ARIMA/005 ARIMA in Code.mp4 127.5 MB
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06 Deep Learning_ Artificial Neural Networks (ANN)/005 Activation Functions.mp4 90.7 MB
05 Machine Learning Methods/009 Machine Learning for Time Series Forecasting in Code (pt 1).mp4 90.4 MB
12 Effective Learning Strategies for Machine Learning FAQ/003 Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 83.5 MB
07 Deep Learning_ Convolutional Neural Networks (CNN)/002 What is Convolution_.mp4 82.1 MB
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06 Deep Learning_ Artificial Neural Networks (ANN)/008 Feedforward ANN for Time Series Forecasting Code.mp4 74.4 MB
03 Exponential Smoothing and ETS Methods/008 SES Code.mp4 72.9 MB
11 Extra Help With Python Coding for Beginners FAQ/003 Proof that using Jupyter Notebook is the same as not using it.mp4 72.9 MB
05 Machine Learning Methods/002 Supervised Machine Learning_ Classification and Regression.mp4 72.3 MB
02 Time Series Basics/011 Random Walks and the Random Walk Hypothesis.mp4 71.4 MB
06 Deep Learning_ Artificial Neural Networks (ANN)/009 Feedforward ANN for Stock Return and Price Predictions Code.mp4 71.0 MB
06 Deep Learning_ Artificial Neural Networks (ANN)/013 Human Activity Recognition_ Multi-Input ANN.mp4 70.8 MB
04 ARIMA/017 Auto ARIMA in Code (Sales Data).mp4 68.6 MB
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05-Implement a Naive Bayes Classifier in Python and Scikit-learn to Categorize Text.mp4 16.9 MB
06-Implement Decision Trees in Python with Scikit-learn.mp4 16.6 MB
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02-Predict Categories in Python using Scikit-learn's Logistic Regression module.mp4 12.4 MB
04-Use K-nearest Neighbors To Find Similar Datapoints with Python and Scikit-learn.mp4 11.3 MB
07-Find Clusters of Data with K-means Clustering in Python and Scikit-learn.mp4 9.0 MB
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~Get Your Files Here !/4 Fine-Tuning the Model/26 Configuring confusion tables.mp4 115.9 MB
~Get Your Files Here !/3 Binomial Logistic Regression/16 Constructing MLE.mp4 95.6 MB
~Get Your Files Here !/3 Binomial Logistic Regression/17 Solving MLE.mp4 71.6 MB
~Get Your Files Here !/6 Working in Power BI with R/35 Running R standard visuals.mp4 70.2 MB
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~Get Your Files Here !/4 Fine-Tuning the Model/22 Adding more independent variables.mp4 60.8 MB
~Get Your Files Here !/4 Fine-Tuning the Model/24 Calculating correlations.mp4 60.5 MB
~Get Your Files Here !/5 Multinomial Regression/29 Calculating odds for multinomial models.mp4 59.8 MB
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~Get Your Files Here !/2 Distributions and Probabilities/11 Sigmoid curve.mp4 54.4 MB
~Get Your Files Here !/1 Introduction/05 Working with R.mp4 53.0 MB
~Get Your Files Here !/3 Binomial Logistic Regression/19 Visualizing logistic regression.mp4 52.6 MB
~Get Your Files Here !/3 Binomial Logistic Regression/15 Calculating log likelihood.mp4 46.9 MB
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~Get Your Files Here !/3 Binomial Logistic Regression/14 Working with the logit model.mp4 42.9 MB
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