Torrent Info
Title Frank Kane - Data Science and Machine Learning with Python
Category
Size 2.51GB

Files List
Please note that this page does not hosts or makes available any of the listed filenames. You cannot download any of those files from here.
001 AB Testing Concepts.mp4 42.69MB
001 Activity Linear Regression.mp4 41.08MB
001 BiasVariance Tradeoff.mp4 31.23MB
001 Introduction.mp4 43.99MB
001 K-Nearest-Neighbors Concepts.mp4 19.90MB
001 More to Explore.mp4 45.14MB
001 Supervised vs. Unsupervised Learning, and TrainTest.mp4 47.80MB
001 Types of Data.mp4 34.11MB
001 User-Based Collaborative Filtering.mp4 36.81MB
002 Activity Installing Spark - Part 2.mp4 81.68MB
002 Activity K-Fold Cross-Validation to avoid overfitting.mp4 45.87MB
002 Activity Polynomial Regression.mp4 29.78MB
002 Activity Using KNN to predict a rating for a movie.mp4 59.21MB
002 Activity Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4 22.02MB
002 Bonus Lecture Discounts on Focused MapReduce and Spark Courses..mp4 33.44MB
002 Getting What You Need.mp4 25.22MB
002 Item-Based Collaborative Filtering.mp4 33.56MB
002 Mean, Median, Mode.mp4 28.17MB
002 T-Tests and P-Values.mp4 30.11MB
003 Activity Finding Movie Similarities.mp4 48.48MB
003 Activity Hands-on With T-Tests.mp4 40.06MB
003 Activity Installing Enthought Canopy.mp4 33.42MB
003 Activity Multivariate Regression, and Predicting Car Prices.mp4 40.07MB
003 Activity Using mean, median, and mode in Python.mp4 38.99MB
003 Bayesian Methods Concepts.mp4 19.41MB
003 Data Cleaning and Normalization.mp4 31.90MB
003 Dimensionality Reduction Principal Component Analysis.mp4 35.67MB
003 Spark Introduction.mp4 32.46MB
004 Activity Cleaning web log data.mp4 60.16MB
004 Activity Implementing a Spam Classifier with Naive Bayes.mp4 36.48MB
004 Activity Improving the Results of Movie Similarities.mp4 43.98MB
004 Activity PCA Example with the Iris data set.mp4 53.31MB
004 Activity Variation and Standard Deviation.mp4 45.62MB
004 Determining How Long to Run an Experiment.mp4 16.68MB
004 Multi-Level Models.mp4 23.66MB
004 Python Basics, Part 1.mp4 43.97MB
004 Spark and the Resilient Distributed Dataset RDD.mp4 36.41MB
005 AB Test Gotchas.mp4 43.78MB
005 Activity Making Movie Recommendations to People.mp4 63.25MB
005 Activity Python Basics, Part 2.mp4 28.46MB
005 Data Warehousing Overview ETL and ELT.mp4 54.11MB
005 Introducing MLLib.mp4 26.27MB
005 K-Means Clustering.mp4 30.30MB
005 Normalizing numerical data.mp4 19.02MB
005 Probability Density Function Probability Mass Function.mp4 12.35MB
006 Activity Clustering people based on income and age.mp4 23.98MB
006 Activity Decision Trees in Spark.mp4 88.24MB
006 Activity Detecting outliers.mp4 39.04MB
006 Common Data Distributions.mp4 27.67MB
006 Exercise Improve the recommenders results.mp4 45.85MB
006 Reinforcement Learning.mp4 63.56MB
006 Running Python Scripts.mp4 21.57MB
007 Activity K-Means Clustering in Spark.mp4 62.85MB
007 Activity Percentiles and Moments.mp4 42.98MB
007 Measuring Entropy.mp4 17.48MB
008 Activity A Crash Course in matplotlib.mp4 49.28MB
008 Decision Trees Concepts.mp4 39.72MB
008 TF IDF.mp4 32.20MB
009 Activity Covariance and Correlation.mp4 49.78MB
009 Activity Decision Trees Predicting Hiring Decisions.mp4 38.23MB
009 Activity Searching Wikipedia with Spark.mp4 59.76MB
010 Ensemble Learning.mp4 33.70MB
010 Exercise Conditional Probability.mp4 52.81MB
011 Exercise Solution Conditional Probability of Purchase by Age.mp4 14.09MB
011 Support Vector Machines SVM Overview.mp4 21.77MB
012 Activity Using SVM to cluster people using scikit-learn.mp4 20.84MB
012 Bayes Theorem.mp4 30.13MB
Distribution statistics by country
Russia (RU) 5
Bulgaria (BG) 1
Ukraine (UA) 1
Belarus (BY) 1
Total 8
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