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| 0. (1Hack.Us) Premium Tutorials-Guides-Articles _ Community based Forum.url |
377б |
| 1. (FreeCoursesOnline.Me) Download Udacity, Masterclass, Lynda, PHLearn, Pluralsight Free.url |
286б |
| 3. (FTUApps.com) Download Cracked Developers Applications For Free.url |
239б |
| How you can help our Group!.txt |
204б |
| U01M01 The basics.mp4 |
34.68Мб |
| U01M02 Machine Learning versus Artificial Intelligence.mp4 |
33.01Мб |
| U01M03 Supervised learning.mp4 |
43.06Мб |
| U01M04 Unsupervised learning.mp4 |
16.22Мб |
| U01M05 Reinforcement learning.mp4 |
28.40Мб |
| U01M06 A quick math refresher.mp4 |
11.02Мб |
| U01M07 Slope of a line.mp4 |
45.10Мб |
| U01M08 Scalars, vectors, and tensors.mp4 |
26.47Мб |
| U01M09 Matrices and matrix arithmetic.mp4 |
13.44Мб |
| U01M10 Set up your computing environment.mp4 |
1.83Мб |
| U01M11 Install Python tools.mp4 |
11.18Мб |
| U01M12 Create virtualenv environment.mp4 |
5.88Мб |
| U01M13 Install Tensorflow.mp4 |
18.31Мб |
| U01M14 The projects.mp4 |
10.06Мб |
| U02M01 Supervised learning.mp4 |
22.32Мб |
| U02M02 Trend lines.mp4 |
4.62Мб |
| U02M03 Cost functions.mp4 |
3.80Мб |
| U02M04 Minimizing cost functions.mp4 |
8.78Мб |
| U02M05 Visualizing data.mp4 |
34.97Мб |
| U02M06 Using linear regression to predict values.mp4 |
22.84Мб |
| U02M07 More complicated functions.mp4 |
1.71Мб |
| U02M08 Working with matrices.mp4 |
4.61Мб |
| U02M09 Letting Tensorflow do the hard work.mp4 |
14.17Мб |
| U03M01 More supervised learning.mp4 |
4.72Мб |
| U03M02 What are features_.mp4 |
5.63Мб |
| U03M03 What makes a good feature_.mp4 |
15.53Мб |
| U03M04 Decision trees.mp4 |
10.58Мб |
| U03M05 K-nearest neighbor.mp4 |
9.92Мб |
| U03M06 Linear classification.mp4 |
7.89Мб |
| U03M07 Making it work in Tensorflow.mp4 |
21.22Мб |
| U03M08 Creating a spam filter.mp4 |
13.66Мб |
| U03M09 Tools and data for email classification.mp4 |
36.00Мб |
| U03M10 Classifying emails.mp4 |
9.15Мб |
| U04M01 How clustering works.mp4 |
82.12Мб |
| U04M02 Clustering algorithms.mp4 |
56.82Мб |
| U04M03 Introducing k-means.mp4 |
56.87Мб |
| U04M06 Assigning Points to a Centroid in K-means).mp4 |
34.33Мб |
| U05M01 What are neural networks, and how do they work.mp4 |
68.70Мб |
| U05M02 The Tensorflow Playground interface.mp4 |
14.04Мб |
| U05M03 Adding nodes to use multiple models in the TensorFlow Playground.mp4 |
12.81Мб |
| U05M04 What hidden layers are, and how to use them with TensorFlow Playground.mp4 |
43.92Мб |
| U05M05 What is the activation function in a neural network_.mp4 |
35.82Мб |
| U06M01 Using Neural Networks.mp4 |
56.56Мб |
| U06M02 How encoding non-numeric data works.mp4 |
64.84Мб |
| U06M03 One hot encoding.mp4 |
84.50Мб |
| U06M04 How image recognition relates to a neural network.mp4 |
95.14Мб |
| U07M01 Encoding and Representation.mp4 |
21.27Мб |
| U07M02 Numeric representation of data.mp4 |
40.61Мб |
| U07M03 Text representation of data.mp4 |
31.82Мб |
| U07M04 Representation of image data.mp4 |
34.06Мб |
| U07M05 Representation of audio data.mp4 |
28.39Мб |
| U07M06 Analytics, stock prices, and other time series data.mp4 |
43.63Мб |
| U07M07 Preparing data_ finding the data set.mp4 |
31.31Мб |
| U07M08 Preparing data_ Features engineering.mp4 |
61.38Мб |
| U07M09 Principal Component Analysis_ The mathematical way to determine features.mp4 |
23.11Мб |
| U07M10 Feature selection.mp4 |
34.54Мб |
| U07M11 Geometry of the data space and the curse of dimensionality.mp4 |
58.61Мб |
| U08M01 The difference between an algorithm and a model.mp4 |
50.27Мб |
| U08M02 Chaining together models.mp4 |
146.62Мб |
| U09M01 Improving performance in machine learning routines.mp4 |
89.81Мб |
| U09M02 Using parallelization.mp4 |
57.25Мб |
| U09M03 Outliers.mp4 |
204.64Мб |
| U09M05 What should we do with outliers_.mp4 |
119.10Мб |
| U09M06 Robustness and noise.mp4 |
40.25Мб |
| U09M07 Overfitting.mp4 |
104.22Мб |
| U09M08 Regularization.mp4 |
272.46Мб |