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| 001 AB Testing Concepts.mp4 |
42.69Мб |
| 001 Activity Linear Regression.mp4 |
41.08Мб |
| 001 BiasVariance Tradeoff.mp4 |
31.23Мб |
| 001 Introduction.mp4 |
43.99Мб |
| 001 K-Nearest-Neighbors Concepts.mp4 |
19.90Мб |
| 001 More to Explore.mp4 |
45.14Мб |
| 001 Supervised vs. Unsupervised Learning, and TrainTest.mp4 |
47.80Мб |
| 001 Types of Data.mp4 |
34.11Мб |
| 001 User-Based Collaborative Filtering.mp4 |
36.81Мб |
| 002 Activity Installing Spark - Part 2.mp4 |
81.68Мб |
| 002 Activity K-Fold Cross-Validation to avoid overfitting.mp4 |
45.87Мб |
| 002 Activity Polynomial Regression.mp4 |
29.78Мб |
| 002 Activity Using KNN to predict a rating for a movie.mp4 |
59.21Мб |
| 002 Activity Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4 |
22.02Мб |
| 002 Bonus Lecture Discounts on Focused MapReduce and Spark Courses..mp4 |
33.44Мб |
| 002 Getting What You Need.mp4 |
25.22Мб |
| 002 Item-Based Collaborative Filtering.mp4 |
33.56Мб |
| 002 Mean, Median, Mode.mp4 |
28.17Мб |
| 002 T-Tests and P-Values.mp4 |
30.11Мб |
| 003 Activity Finding Movie Similarities.mp4 |
48.48Мб |
| 003 Activity Hands-on With T-Tests.mp4 |
40.06Мб |
| 003 Activity Installing Enthought Canopy.mp4 |
33.42Мб |
| 003 Activity Multivariate Regression, and Predicting Car Prices.mp4 |
40.07Мб |
| 003 Activity Using mean, median, and mode in Python.mp4 |
38.99Мб |
| 003 Bayesian Methods Concepts.mp4 |
19.41Мб |
| 003 Data Cleaning and Normalization.mp4 |
31.90Мб |
| 003 Dimensionality Reduction Principal Component Analysis.mp4 |
35.67Мб |
| 003 Spark Introduction.mp4 |
32.46Мб |
| 004 Activity Cleaning web log data.mp4 |
60.16Мб |
| 004 Activity Implementing a Spam Classifier with Naive Bayes.mp4 |
36.48Мб |
| 004 Activity Improving the Results of Movie Similarities.mp4 |
43.98Мб |
| 004 Activity PCA Example with the Iris data set.mp4 |
53.31Мб |
| 004 Activity Variation and Standard Deviation.mp4 |
45.62Мб |
| 004 Determining How Long to Run an Experiment.mp4 |
16.68Мб |
| 004 Multi-Level Models.mp4 |
23.66Мб |
| 004 Python Basics, Part 1.mp4 |
43.97Мб |
| 004 Spark and the Resilient Distributed Dataset RDD.mp4 |
36.41Мб |
| 005 AB Test Gotchas.mp4 |
43.78Мб |
| 005 Activity Making Movie Recommendations to People.mp4 |
63.25Мб |
| 005 Activity Python Basics, Part 2.mp4 |
28.46Мб |
| 005 Data Warehousing Overview ETL and ELT.mp4 |
54.11Мб |
| 005 Introducing MLLib.mp4 |
26.27Мб |
| 005 K-Means Clustering.mp4 |
30.30Мб |
| 005 Normalizing numerical data.mp4 |
19.02Мб |
| 005 Probability Density Function Probability Mass Function.mp4 |
12.35Мб |
| 006 Activity Clustering people based on income and age.mp4 |
23.98Мб |
| 006 Activity Decision Trees in Spark.mp4 |
88.24Мб |
| 006 Activity Detecting outliers.mp4 |
39.04Мб |
| 006 Common Data Distributions.mp4 |
27.67Мб |
| 006 Exercise Improve the recommenders results.mp4 |
45.85Мб |
| 006 Reinforcement Learning.mp4 |
63.56Мб |
| 006 Running Python Scripts.mp4 |
21.57Мб |
| 007 Activity K-Means Clustering in Spark.mp4 |
62.85Мб |
| 007 Activity Percentiles and Moments.mp4 |
42.98Мб |
| 007 Measuring Entropy.mp4 |
17.48Мб |
| 008 Activity A Crash Course in matplotlib.mp4 |
49.28Мб |
| 008 Decision Trees Concepts.mp4 |
39.72Мб |
| 008 TF IDF.mp4 |
32.20Мб |
| 009 Activity Covariance and Correlation.mp4 |
49.78Мб |
| 009 Activity Decision Trees Predicting Hiring Decisions.mp4 |
38.23Мб |
| 009 Activity Searching Wikipedia with Spark.mp4 |
59.76Мб |
| 010 Ensemble Learning.mp4 |
33.70Мб |
| 010 Exercise Conditional Probability.mp4 |
52.81Мб |
| 011 Exercise Solution Conditional Probability of Purchase by Age.mp4 |
14.09Мб |
| 011 Support Vector Machines SVM Overview.mp4 |
21.77Мб |
| 012 Activity Using SVM to cluster people using scikit-learn.mp4 |
20.84Мб |
| 012 Bayes Theorem.mp4 |
30.13Мб |