[CourseClub.Me] O`REILLY - Data Science Bookcamp, video edition - 磁力管家

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最近下载：2025-05-15
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文档列表

113 - Chapter 21. Measuring feature importance with coefficients.mp4 97.7 MB
71 - Chapter 15. Clustering texts by topic, Part 2.mp4 91.3 MB
66 - Chapter 15. Vectorizing documents using scikit-learn.mp4 91.3 MB
86 - Case study 5 - Predicting future friendships from social network data.mp4 84.3 MB
23 - Chapter 7. Data dredging - Coming to false conclusions through oversampling.mp4 83.8 MB
14 - Chapter 5. Basic probability and statistical analysis using SciPy.mp4 79.9 MB
98 - Chapter 19. Community detection using Markov clustering, Part 2.mp4 78.9 MB
93 - Chapter 19. Dynamic graph theory techniques for node ranking and social network analysis.mp4 78.7 MB
87 - Chapter 18. An introduction to graph theory and network analysis.mp4 78.5 MB
16 - Chapter 5. Variance as a measure of dispersion.mp4 77.5 MB
70 - Chapter 15. Clustering texts by topic, Part 1.mp4 76.9 MB
109 - Chapter 21. Training a linear classifier, Part 2.mp4 76.8 MB
81 - Chapter 17. Filtering jobs by relevance.mp4 76.7 MB
44 - Chapter 12. Visualizing and clustering the extracted location data.mp4 74.2 MB
84 - Chapter 17. Exploring clusters at alternative values of K.mp4 72.7 MB
42 - Chapter 11. Limitations of the GeoNamesCache library.mp4 72.5 MB
36 - Chapter 10. Clustering based on non-Euclidean distance.mp4 72.1 MB
64 - Chapter 14. Efficient dimension reduction using SVD and scikit-learn.mp4 71.9 MB
22 - Chapter 7. Assessing the divergence between sample mean and population mean.mp4 71.6 MB
82 - Chapter 17. Clustering skills in relevant job postings.mp4 69.8 MB
5 - Chapter 2. Comparing multiple coin-flip probability distributions.mp4 68.8 MB
114 - Chapter 22. Training nonlinear classifiers with decision tree techniques.mp4 68.4 MB
58 - Chapter 14. Dimension reduction using PCA and scikit-learn.mp4 67.9 MB
20 - Chapter 6. Computing the area beneath a normal curve.mp4 67.7 MB
128 - Chapter 23. Interpreting the trained model.mp4 67.3 MB
106 - Chapter 20. Limitations of the KNN algorithm.mp4 66.2 MB
76 - Chapter 16. The structure of HTML documents.mp4 66.0 MB
41 - Chapter 11. Location tracking using GeoNamesCache.mp4 65.4 MB
126 - Chapter 23. Adding profile features to the model.mp4 65.0 MB
55 - Chapter 14. Dimension reduction of matrix data.mp4 64.7 MB
33 - Chapter 10. Clustering data into groups.mp4 64.4 MB
34 - Chapter 10. K-means - A clustering algorithm for grouping data into K central groups.mp4 64.2 MB
3 - Chapter 1. Problem 2 - Analyzing multiple die rolls.mp4 63.8 MB
69 - Chapter 15. Computing similarities across large document datasets.mp4 63.2 MB
97 - Chapter 19. Community detection using Markov clustering, Part 1.mp4 63.0 MB
80 - Chapter 17. Exploring the HTML for skill descriptions.mp4 62.5 MB
119 - Chapter 22. Studying cancerous cells using feature importance.mp4 62.2 MB
72 - Chapter 15. Visualizing text clusters.mp4 61.8 MB
74 - Chapter 15. Using subplots to display multiple word clouds, Part 2.mp4 61.7 MB
17 - Chapter 6. Making predictions using the central limit theorem and SciPy.mp4 61.5 MB
40 - Chapter 11. Visualizing maps.mp4 61.1 MB
107 - Chapter 21. Training linear classifiers with logistic regression.mp4 61.1 MB
99 - Chapter 19. Uncovering friend groups in social networks.mp4 60.8 MB
117 - Chapter 22. Training if_else models with more than two features.mp4 60.6 MB
8 - Chapter 3. Deriving probabilities from histograms.mp4 60.4 MB
90 - Chapter 18. Utilizing undirected graphs to optimize the travel time between towns.mp4 60.2 MB
120 - Chapter 22. Improving performance using random forest classification.mp4 60.2 MB
116 - Chapter 22. Deciding which feature to split on.mp4 60.0 MB
2 - Chapter 1. Computing probabilities using Python This section covers.mp4 59.5 MB
67 - Chapter 15. Ranking words by both post frequency and count, Part 1.mp4 59.3 MB
103 - Chapter 20. Measuring predicted label accuracy, Part 2.mp4 57.9 MB
19 - Chapter 6. Determining the mean and variance of a population through random sampling.mp4 57.9 MB
59 - Chapter 14. Clustering 4D data in two dimensions.mp4 57.1 MB
125 - Chapter 23. Training a predictive model using network features, Part 2.mp4 56.5 MB
4 - Chapter 2. Plotting probabilities using Matplotlib.mp4 56.4 MB
24 - Chapter 7. Bootstrapping with replacement - Testing a hypothesis when the population variance is unknown 1.mp4 55.9 MB
115 - Chapter 22. Training a nested if_else model using two features.mp4 55.8 MB
89 - Chapter 18. Analyzing web networks using NetworkX, Part 2.mp4 55.6 MB
9 - Chapter 3. Computing histograms in NumPy.mp4 55.6 MB
121 - Chapter 22. Training random forest classifiers using scikit-learn.mp4 55.5 MB
25 - Chapter 7. Bootstrapping with replacement - Testing a hypothesis when the population variance is unknown 2.mp4 55.3 MB
124 - Chapter 23. Training a predictive model using network features, Part 1.mp4 55.1 MB
35 - Chapter 10. Using density to discover clusters.mp4 54.8 MB
118 - Chapter 22. Training decision tree classifiers using scikit-learn.mp4 54.4 MB
73 - Chapter 15. Using subplots to display multiple word clouds, Part 1.mp4 53.0 MB
112 - Chapter 21. Training linear classifiers using scikit-learn.mp4 52.1 MB
101 - Chapter 20. The basics of supervised machine learning.mp4 51.6 MB
92 - Chapter 18. Computing the fastest travel time between nodes, Part 2.mp4 51.4 MB
100 - Chapter 20. Network-driven supervised machine learning.mp4 51.3 MB
52 - Chapter 13. Basic matrix operations, Part 1.mp4 51.1 MB
50 - Chapter 13. Using normalization to improve TF vector similarity.mp4 50.9 MB
95 - Chapter 19. Deriving PageRank centrality from probability theory.mp4 50.7 MB
68 - Chapter 15. Ranking words by both post frequency and count, Part 2.mp4 50.5 MB
54 - Chapter 13. Computational limits of matrix multiplication.mp4 50.1 MB
61 - Chapter 14. Computing principal components without rotation.mp4 50.1 MB
7 - Chapter 3. Computing confidence intervals using histograms and NumPy arrays.mp4 49.9 MB
65 - Chapter 15. NLP analysis of large text datasets.mp4 49.5 MB
12 - Chapter 4. Optimizing strategies using the sample space for a 10-card deck.mp4 49.4 MB
78 - Chapter 16. Parsing HTML using Beautiful Soup, Part 2.mp4 49.0 MB
38 - Chapter 11. Geographic location visualization and analysis.mp4 48.8 MB
62 - Chapter 14. Extracting eigenvectors using power iteration, Part 1.mp4 46.8 MB
96 - Chapter 19. Computing PageRank centrality using NetworkX.mp4 46.8 MB
49 - Chapter 13. Vectorizing texts using word counts.mp4 46.7 MB
47 - Chapter 13. Simple text comparison.mp4 46.1 MB
26 - Chapter 7. Permutation testing - Comparing means of samples when the population parameters are unknown.mp4 45.8 MB
31 - Chapter 9. Determining statistical significance.mp4 45.7 MB
108 - Chapter 21. Training a linear classifier, Part 1.mp4 45.6 MB
110 - Chapter 21. Improving linear classification with logistic regression, Part 1.mp4 45.5 MB
111 - Chapter 21. Improving linear classification with logistic regression, Part 2.mp4 45.2 MB
127 - Chapter 23. Optimizing performance across a steady set of features.mp4 44.6 MB
48 - Chapter 13. Replacing words with numeric values.mp4 44.1 MB
51 - Chapter 13. Using unit vector dot products to convert between relevance metrics.mp4 43.7 MB
83 - Chapter 17. Investigating the technical skill clusters.mp4 43.5 MB
85 - Chapter 17. Analyzing the 700 most relevant postings.mp4 42.9 MB
27 - Chapter 8. Analyzing tables using Pandas.mp4 42.9 MB
37 - Chapter 10. Analyzing clusters using Pandas.mp4 42.5 MB
77 - Chapter 16. Parsing HTML using Beautiful Soup, Part 1.mp4 42.4 MB
29 - Chapter 8. Saving and loading table data.mp4 42.2 MB
94 - Chapter 19. Computing travel probabilities using matrix multiplication.mp4 42.2 MB
75 - Chapter 16. Extracting text from web pages.mp4 41.5 MB
105 - Chapter 20. Running a grid search using scikit-learn.mp4 41.2 MB
21 - Chapter 7. Statistical hypothesis testing.mp4 41.1 MB
123 - Chapter 23. Exploring the experimental observations.mp4 40.9 MB
56 - Chapter 14. Reducing dimensions using rotation, Part 1.mp4 40.9 MB
28 - Chapter 8. Retrieving table rows.mp4 40.1 MB
57 - Chapter 14. Reducing dimensions using rotation, Part 2.mp4 39.4 MB
79 - Chapter 17. Case study 4 solution.mp4 39.2 MB
102 - Chapter 20. Measuring predicted label accuracy, Part 1.mp4 39.1 MB
15 - Chapter 5. Mean as a measure of centrality.mp4 38.4 MB
6 - Chapter 3. Running random simulations in NumPy.mp4 38.1 MB
46 - Chapter 13. Measuring text similarities.mp4 38.0 MB
104 - Chapter 20. Optimizing KNN performance.mp4 37.4 MB
10 - Chapter 3. Using permutations to shuffle cards.mp4 37.1 MB
43 - Chapter 12. Case study 3 solution.mp4 36.3 MB
63 - Chapter 14. Extracting eigenvectors using power iteration, Part 2.mp4 36.1 MB
11 - Chapter 4. Case study 1 solution.mp4 35.9 MB
30 - Chapter 9. Case study 2 solution.mp4 35.2 MB
39 - Chapter 11. Plotting maps using Cartopy.mp4 34.8 MB
122 - Chapter 23. Case study 5 solution.mp4 34.5 MB
91 - Chapter 18. Computing the fastest travel time between nodes, Part 1.mp4 33.7 MB
18 - Chapter 6. Comparing two sampled normal curves.mp4 33.0 MB
13 - Case study 2 - Assessing online ad clicks for significance.mp4 32.9 MB
88 - Chapter 18. Analyzing web networks using NetworkX, Part 1.mp4 32.4 MB
60 - Chapter 14. Limitations of PCA.mp4 32.3 MB
53 - Chapter 13. Basic matrix operations, Part 2.mp4 28.5 MB
45 - Case study 4 - Using online job postings to improve your data science resume.mp4 25.1 MB
1 - Case study 1 - Finding the winning strategy in a card game.mp4 7.2 MB
32 - Case study 3 - Tracking disease outbreaks using news headlines.mp4 6.9 MB
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