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[FreeCoursesOnline.Me] MANNING - Machine Learning for Mere Mortals

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0. Websites you may like/How you can help our Group!.txt
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U01M01 The basics.mp4
35 MB
U01M02 Machine Learning versus Artificial Intelligence.mp4
33 MB
U01M03 Supervised learning.mp4
43 MB
U01M04 Unsupervised learning.mp4
16 MB
U01M05 Reinforcement learning.mp4
28 MB
U01M06 A quick math refresher.mp4
11 MB
U01M07 Slope of a line.mp4
45 MB
U01M08 Scalars, vectors, and tensors.mp4
26 MB
U01M09 Matrices and matrix arithmetic.mp4
13 MB
U01M10 Set up your computing environment.mp4
1.8 MB
U01M11 Install Python tools.mp4
11 MB
U01M12 Create virtualenv environment.mp4
5.9 MB
U01M13 Install Tensorflow.mp4
18 MB
U01M14 The projects.mp4
10 MB
U02M01 Supervised learning.mp4
22 MB
U02M02 Trend lines.mp4
4.6 MB
U02M03 Cost functions.mp4
3.8 MB
U02M04 Minimizing cost functions.mp4
8.8 MB
U02M05 Visualizing data.mp4
35 MB
U02M06 Using linear regression to predict values.mp4
23 MB
U02M07 More complicated functions.mp4
1.7 MB
U02M08 Working with matrices.mp4
4.6 MB
U02M09 Letting Tensorflow do the hard work.mp4
14 MB
U03M01 More supervised learning.mp4
4.7 MB
U03M02 What are features_.mp4
5.6 MB
U03M03 What makes a good feature_.mp4
16 MB
U03M04 Decision trees.mp4
11 MB
U03M05 K-nearest neighbor.mp4
9.9 MB
U03M06 Linear classification.mp4
7.9 MB
U03M07 Making it work in Tensorflow.mp4
21 MB
U03M08 Creating a spam filter.mp4
14 MB
U03M09 Tools and data for email classification.mp4
36 MB
U03M10 Classifying emails.mp4
9.2 MB
U04M01 How clustering works.mp4
82 MB
U04M02 Clustering algorithms.mp4
57 MB
U04M03 Introducing k-means.mp4
57 MB
U04M06 Assigning Points to a Centroid in K-means).mp4
34 MB
U05M01 What are neural networks, and how do they work.mp4
69 MB
U05M02 The Tensorflow Playground interface.mp4
14 MB
U05M03 Adding nodes to use multiple models in the TensorFlow Playground.mp4
13 MB
U05M04 What hidden layers are, and how to use them with TensorFlow Playground.mp4
44 MB
U05M05 What is the activation function in a neural network_.mp4
36 MB
U06M01 Using Neural Networks.mp4
57 MB
U06M02 How encoding non-numeric data works.mp4
65 MB
U06M03 One hot encoding.mp4
84 MB
U06M04 How image recognition relates to a neural network.mp4
95 MB
U07M01 Encoding and Representation.mp4
21 MB
U07M02 Numeric representation of data.mp4
41 MB
U07M03 Text representation of data.mp4
32 MB
U07M04 Representation of image data.mp4
34 MB
U07M05 Representation of audio data.mp4
28 MB
U07M06 Analytics, stock prices, and other time series data.mp4
44 MB
U07M07 Preparing data_ finding the data set.mp4
31 MB
U07M08 Preparing data_ Features engineering.mp4
61 MB
U07M09 Principal Component Analysis_ The mathematical way to determine features.mp4
23 MB
U07M10 Feature selection.mp4
34 MB
U07M11 Geometry of the data space and the curse of dimensionality.mp4
59 MB
U08M01 The difference between an algorithm and a model.mp4
50 MB
U08M02 Chaining together models.mp4
147 MB
U09M01 Improving performance in machine learning routines.mp4
90 MB
U09M02 Using parallelization.mp4
57 MB
U09M03 Outliers.mp4
205 MB
U09M05 What should we do with outliers_.mp4
119 MB
U09M06 Robustness and noise.mp4
40 MB
U09M07 Overfitting.mp4
104 MB
U09M08 Regularization.mp4
272 MB