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06 Supervised Learning - Regression/008 Random Forest Model Development.mp4 258.2 MB
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05 Supervised Learning - Classification/004 k-NN Training-Set and Test-Set Creation.mp4 239.5 MB
03 Data Preprocessing/006 Missing Values2.mp4 230.0 MB
06 Supervised Learning - Regression/006 Polynomial Linear Regression Model Development.mp4 229.8 MB
06 Supervised Learning - Regression/001 Simple and Multiple Linear Regression Concepts.mp4 222.5 MB
03 Data Preprocessing/003 Statistics2.mp4 217.6 MB
02 Machine Learning Useful Packages (Libraries)/013 Visualization with Matplotlib2.mp4 215.2 MB
02 Machine Learning Useful Packages (Libraries)/011 Pandas4.mp4 212.9 MB
02 Machine Learning Useful Packages (Libraries)/014 Visualization with Matplotlib3.mp4 198.0 MB
03 Data Preprocessing/012 Normalization.mp4 195.9 MB
05 Supervised Learning - Classification/013 Model Evaluation - Calculating with Python.mp4 182.5 MB
06 Supervised Learning - Regression/004 Evaluation Metrics - Implementation.mp4 167.7 MB
03 Data Preprocessing/001 Reading and Modifying a Dataset.mp4 162.1 MB
02 Machine Learning Useful Packages (Libraries)/006 NumPy5.mp4 160.1 MB
07 Unsupervised Learning - Clustering Techniques/010 Hierarchical Clustering Model Development.mp4 153.0 MB
02 Machine Learning Useful Packages (Libraries)/015 Visualization with Matplotlib4.mp4 149.9 MB
05 Supervised Learning - Classification/003 k-NN Model Development.mp4 147.5 MB
02 Machine Learning Useful Packages (Libraries)/007 NumPy6.mp4 141.0 MB
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[TutsNode.com] - Excel for Data Science and Machine Learning/4. Logistic Regression/4. Applying Logistic Regression in Excel.mp4 111.8 MB
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04. Introduction to Optimisation and the Gradient Descent Algorithm/08. [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4 305.5 MB
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10. Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/12. Model Evaluation and the Confusion Matrix.mp4 264.1 MB
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12. Serving a Tensorflow Model through a Website/14. Calculating the Centre of Mass and Shifting the Image.mp4 234.1 MB
04. Introduction to Optimisation and the Gradient Descent Algorithm/09. [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4 229.6 MB
10. Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/10. Use the Model to Make Predictions.mp4 228.9 MB
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11. Use Tensorflow to Classify Handwritten Digits/12. Different Model Architectures Experimenting with Dropout.mp4 224.1 MB
08. Test and Evaluate a Naive Bayes Classifier Part 3/06. Visualising the Decision Boundary.mp4 215.3 MB
08. Test and Evaluate a Naive Bayes Classifier Part 3/11. A Naive Bayes Implementation using SciKit Learn.mp4 204.6 MB
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