Frank Kane - Data Science and Machine Learning with Python

1. 01 Getting Started/001 Introduction.mp443.99MB
2. 01 Getting Started/004 Python Basics, Part 1.mp443.97MB
3. 01 Getting Started/003 Activity Installing Enthought Canopy.mp433.42MB
4. 01 Getting Started/005 Activity Python Basics, Part 2.mp428.46MB
5. 01 Getting Started/002 Getting What You Need.mp425.22MB
6. 01 Getting Started/006 Running Python Scripts.mp421.57MB
7. 02 Statistics and Probability Refresher, and Python Practise/010 Exercise Conditional Probability.mp452.81MB
8. 02 Statistics and Probability Refresher, and Python Practise/009 Activity Covariance and Correlation.mp449.78MB
9. 02 Statistics and Probability Refresher, and Python Practise/008 Activity A Crash Course in matplotlib.mp449.28MB
10. 02 Statistics and Probability Refresher, and Python Practise/004 Activity Variation and Standard Deviation.mp445.62MB
11. 02 Statistics and Probability Refresher, and Python Practise/007 Activity Percentiles and Moments.mp442.98MB
12. 02 Statistics and Probability Refresher, and Python Practise/003 Activity Using mean, median, and mode in Python.mp438.99MB
13. 02 Statistics and Probability Refresher, and Python Practise/001 Types of Data.mp434.11MB
14. 02 Statistics and Probability Refresher, and Python Practise/012 Bayes Theorem.mp430.13MB
15. 02 Statistics and Probability Refresher, and Python Practise/002 Mean, Median, Mode.mp428.17MB
16. 02 Statistics and Probability Refresher, and Python Practise/006 Common Data Distributions.mp427.67MB
17. 02 Statistics and Probability Refresher, and Python Practise/011 Exercise Solution Conditional Probability of Purchase by Age.mp414.09MB
18. 02 Statistics and Probability Refresher, and Python Practise/005 Probability Density Function Probability Mass Function.mp412.35MB
19. 03 Predictive Models/001 Activity Linear Regression.mp441.08MB
20. 03 Predictive Models/003 Activity Multivariate Regression, and Predicting Car Prices.mp440.07MB
21. 03 Predictive Models/002 Activity Polynomial Regression.mp429.78MB
22. 03 Predictive Models/004 Multi-Level Models.mp423.66MB
23. 04 Machine Learning with Python/001 Supervised vs. Unsupervised Learning, and TrainTest.mp447.8MB
24. 04 Machine Learning with Python/008 Decision Trees Concepts.mp439.72MB
25. 04 Machine Learning with Python/009 Activity Decision Trees Predicting Hiring Decisions.mp438.23MB
26. 04 Machine Learning with Python/004 Activity Implementing a Spam Classifier with Naive Bayes.mp436.48MB
27. 04 Machine Learning with Python/010 Ensemble Learning.mp433.7MB
28. 04 Machine Learning with Python/005 K-Means Clustering.mp430.3MB
29. 04 Machine Learning with Python/006 Activity Clustering people based on income and age.mp423.98MB
30. 04 Machine Learning with Python/002 Activity Using TrainTest to Prevent Overfitting a Polynomial Regression.mp422.02MB
31. 04 Machine Learning with Python/011 Support Vector Machines SVM Overview.mp421.77MB
32. 04 Machine Learning with Python/012 Activity Using SVM to cluster people using scikit-learn.mp420.84MB
33. 04 Machine Learning with Python/003 Bayesian Methods Concepts.mp419.41MB
34. 04 Machine Learning with Python/007 Measuring Entropy.mp417.48MB
35. 05 Recommender Systems/005 Activity Making Movie Recommendations to People.mp463.25MB
36. 05 Recommender Systems/003 Activity Finding Movie Similarities.mp448.48MB
37. 05 Recommender Systems/006 Exercise Improve the recommenders results.mp445.85MB
38. 05 Recommender Systems/004 Activity Improving the Results of Movie Similarities.mp443.98MB
39. 05 Recommender Systems/001 User-Based Collaborative Filtering.mp436.81MB
40. 05 Recommender Systems/002 Item-Based Collaborative Filtering.mp433.56MB
41. 06 More Data Mining and Machine Learning Techniques/006 Reinforcement Learning.mp463.56MB
42. 06 More Data Mining and Machine Learning Techniques/002 Activity Using KNN to predict a rating for a movie.mp459.21MB
43. 06 More Data Mining and Machine Learning Techniques/005 Data Warehousing Overview ETL and ELT.mp454.11MB
44. 06 More Data Mining and Machine Learning Techniques/004 Activity PCA Example with the Iris data set.mp453.31MB
45. 06 More Data Mining and Machine Learning Techniques/003 Dimensionality Reduction Principal Component Analysis.mp435.67MB
46. 06 More Data Mining and Machine Learning Techniques/001 K-Nearest-Neighbors Concepts.mp419.9MB
47. 07 Dealing with Real-World Data/004 Activity Cleaning web log data.mp460.16MB
48. 07 Dealing with Real-World Data/002 Activity K-Fold Cross-Validation to avoid overfitting.mp445.87MB
49. 07 Dealing with Real-World Data/006 Activity Detecting outliers.mp439.04MB
50. 07 Dealing with Real-World Data/003 Data Cleaning and Normalization.mp431.9MB
51. 07 Dealing with Real-World Data/001 BiasVariance Tradeoff.mp431.23MB
52. 07 Dealing with Real-World Data/005 Normalizing numerical data.mp419.02MB
53. 08 Apache Spark Machine Learning on Big Data/006 Activity Decision Trees in Spark.mp488.24MB
54. 08 Apache Spark Machine Learning on Big Data/002 Activity Installing Spark - Part 2.mp481.68MB
55. 08 Apache Spark Machine Learning on Big Data/007 Activity K-Means Clustering in Spark.mp462.85MB
56. 08 Apache Spark Machine Learning on Big Data/009 Activity Searching Wikipedia with Spark.mp459.76MB
57. 08 Apache Spark Machine Learning on Big Data/004 Spark and the Resilient Distributed Dataset RDD.mp436.41MB
58. 08 Apache Spark Machine Learning on Big Data/003 Spark Introduction.mp432.46MB
59. 08 Apache Spark Machine Learning on Big Data/008 TF IDF.mp432.2MB
60. 08 Apache Spark Machine Learning on Big Data/005 Introducing MLLib.mp426.27MB
61. 09 Experimental Design/005 AB Test Gotchas.mp443.78MB
62. 09 Experimental Design/001 AB Testing Concepts.mp442.69MB
63. 09 Experimental Design/003 Activity Hands-on With T-Tests.mp440.06MB
64. 09 Experimental Design/002 T-Tests and P-Values.mp430.11MB
65. 09 Experimental Design/004 Determining How Long to Run an Experiment.mp416.68MB
66. 10 You made it/001 More to Explore.mp445.14MB
67. 10 You made it/002 Bonus Lecture Discounts on Focused MapReduce and Spark Courses..mp433.44MB