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[CourseClub.Me] MANNING - Machine Learning for Mere Mortals
magnet:?xt=urn:btih:087d7e3105bdc5df58691ea15f6755624350c4ae&dn=[CourseClub.Me] MANNING - Machine Learning for Mere Mortals
磁力链接详情
Hash值:
087d7e3105bdc5df58691ea15f6755624350c4ae
点击数:
165
文件大小:
2.69 GB
文件数量:
66
创建日期:
2021-11-16 00:27
最后访问:
2024-6-30 11:26
访问标签:
CourseClub
Me
MANNING
-
Machine
Learning
for
Mere
Mortals
文件列表详情
U01M01 The basics.mp4 34.68 MB
U01M02 Machine Learning versus Artificial Intelligence.mp4 33.01 MB
U01M03 Supervised learning.mp4 43.06 MB
U01M04 Unsupervised learning.mp4 16.22 MB
U01M05 Reinforcement learning.mp4 28.4 MB
U01M06 A quick math refresher.mp4 11.02 MB
U01M07 Slope of a line.mp4 45.1 MB
U01M08 Scalars, vectors, and tensors.mp4 26.47 MB
U01M09 Matrices and matrix arithmetic.mp4 13.44 MB
U01M10 Set up your computing environment.mp4 1.83 MB
U01M11 Install Python tools.mp4 11.18 MB
U01M12 Create virtualenv environment.mp4 5.88 MB
U01M13 Install Tensorflow.mp4 18.31 MB
U01M14 The projects.mp4 10.06 MB
U02M01 Supervised learning.mp4 22.32 MB
U02M02 Trend lines.mp4 4.62 MB
U02M03 Cost functions.mp4 3.8 MB
U02M04 Minimizing cost functions.mp4 8.78 MB
U02M05 Visualizing data.mp4 34.97 MB
U02M06 Using linear regression to predict values.mp4 22.84 MB
U02M07 More complicated functions.mp4 1.71 MB
U02M08 Working with matrices.mp4 4.61 MB
U02M09 Letting Tensorflow do the hard work.mp4 14.17 MB
U03M01 More supervised learning.mp4 4.72 MB
U03M02 What are features_.mp4 5.63 MB
U03M03 What makes a good feature_.mp4 15.53 MB
U03M04 Decision trees.mp4 10.58 MB
U03M05 K-nearest neighbor.mp4 9.92 MB
U03M06 Linear classification.mp4 7.89 MB
U03M07 Making it work in Tensorflow.mp4 21.22 MB
U03M08 Creating a spam filter.mp4 13.66 MB
U03M09 Tools and data for email classification.mp4 36 MB
U03M10 Classifying emails.mp4 9.15 MB
U04M01 How clustering works.mp4 82.12 MB
U04M02 Clustering algorithms.mp4 56.82 MB
U04M03 Introducing k-means.mp4 56.87 MB
U04M06 Assigning Points to a Centroid in K-means).mp4 34.33 MB
U05M01 What are neural networks, and how do they work.mp4 68.7 MB
U05M02 The Tensorflow Playground interface.mp4 14.04 MB
U05M03 Adding nodes to use multiple models in the TensorFlow Playground.mp4 12.81 MB
U05M04 What hidden layers are, and how to use them with TensorFlow Playground.mp4 43.92 MB
U05M05 What is the activation function in a neural network_.mp4 35.82 MB
U06M01 Using Neural Networks.mp4 56.56 MB
U06M02 How encoding non-numeric data works.mp4 64.84 MB
U06M03 One hot encoding.mp4 84.5 MB
U06M04 How image recognition relates to a neural network.mp4 95.14 MB
U07M01 Encoding and Representation.mp4 21.27 MB
U07M02 Numeric representation of data.mp4 40.61 MB
U07M03 Text representation of data.mp4 31.82 MB
U07M04 Representation of image data.mp4 34.06 MB
U07M05 Representation of audio data.mp4 28.39 MB
U07M06 Analytics, stock prices, and other time series data.mp4 43.63 MB
U07M07 Preparing data_ finding the data set.mp4 31.31 MB
U07M08 Preparing data_ Features engineering.mp4 61.38 MB
U07M09 Principal Component Analysis_ The mathematical way to determine features.mp4 23.11 MB
U07M10 Feature selection.mp4 34.54 MB
U07M11 Geometry of the data space and the curse of dimensionality.mp4 58.61 MB
U08M01 The difference between an algorithm and a model.mp4 50.27 MB
U08M02 Chaining together models.mp4 146.62 MB
U09M01 Improving performance in machine learning routines.mp4 89.81 MB
U09M02 Using parallelization.mp4 57.25 MB
U09M03 Outliers.mp4 204.64 MB
U09M05 What should we do with outliers_.mp4 119.1 MB
U09M06 Robustness and noise.mp4 40.25 MB
U09M07 Overfitting.mp4 104.22 MB
U09M08 Regularization.mp4 272.46 MB
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