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种子名称： Frank Kane - Data Science and Machine Learning with Python
文件类型： 视频
文件数目： 67个文件
文件大小： 2.51 GB
收录时间： 2016-9-15 11:58
已经下载： 3次
资源热度： 123
最近下载： 2025-1-4 08:05

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Frank Kane - Data Science and Machine Learning with Python.torrent

01 Getting Started/001 Introduction.mp443.99MB

01 Getting Started/004 Python Basics, Part 1.mp443.97MB

01 Getting Started/003 Activity Installing Enthought Canopy.mp433.42MB

01 Getting Started/005 Activity Python Basics, Part 2.mp428.46MB

01 Getting Started/002 Getting What You Need.mp425.22MB

01 Getting Started/006 Running Python Scripts.mp421.57MB

02 Statistics and Probability Refresher, and Python Practise/010 Exercise Conditional Probability.mp452.81MB

02 Statistics and Probability Refresher, and Python Practise/009 Activity Covariance and Correlation.mp449.78MB

02 Statistics and Probability Refresher, and Python Practise/008 Activity A Crash Course in matplotlib.mp449.28MB

02 Statistics and Probability Refresher, and Python Practise/004 Activity Variation and Standard Deviation.mp445.62MB

02 Statistics and Probability Refresher, and Python Practise/007 Activity Percentiles and Moments.mp442.98MB

02 Statistics and Probability Refresher, and Python Practise/003 Activity Using mean, median, and mode in Python.mp438.99MB

02 Statistics and Probability Refresher, and Python Practise/001 Types of Data.mp434.11MB

02 Statistics and Probability Refresher, and Python Practise/012 Bayes Theorem.mp430.13MB

02 Statistics and Probability Refresher, and Python Practise/002 Mean, Median, Mode.mp428.17MB

02 Statistics and Probability Refresher, and Python Practise/006 Common Data Distributions.mp427.67MB

02 Statistics and Probability Refresher, and Python Practise/011 Exercise Solution Conditional Probability of Purchase by Age.mp414.09MB

02 Statistics and Probability Refresher, and Python Practise/005 Probability Density Function Probability Mass Function.mp412.35MB

03 Predictive Models/001 Activity Linear Regression.mp441.08MB

03 Predictive Models/003 Activity Multivariate Regression, and Predicting Car Prices.mp440.07MB

03 Predictive Models/002 Activity Polynomial Regression.mp429.78MB

03 Predictive Models/004 Multi-Level Models.mp423.66MB

04 Machine Learning with Python/001 Supervised vs. Unsupervised Learning, and TrainTest.mp447.8MB

04 Machine Learning with Python/008 Decision Trees Concepts.mp439.72MB

04 Machine Learning with Python/009 Activity Decision Trees Predicting Hiring Decisions.mp438.23MB

04 Machine Learning with Python/004 Activity Implementing a Spam Classifier with Naive Bayes.mp436.48MB

04 Machine Learning with Python/010 Ensemble Learning.mp433.7MB

04 Machine Learning with Python/005 K-Means Clustering.mp430.3MB

04 Machine Learning with Python/006 Activity Clustering people based on income and age.mp423.98MB

04 Machine Learning with Python/002 Activity Using TrainTest to Prevent Overfitting a Polynomial Regression.mp422.02MB

04 Machine Learning with Python/011 Support Vector Machines SVM Overview.mp421.77MB

04 Machine Learning with Python/012 Activity Using SVM to cluster people using scikit-learn.mp420.84MB

04 Machine Learning with Python/003 Bayesian Methods Concepts.mp419.41MB

04 Machine Learning with Python/007 Measuring Entropy.mp417.48MB

05 Recommender Systems/005 Activity Making Movie Recommendations to People.mp463.25MB

05 Recommender Systems/003 Activity Finding Movie Similarities.mp448.48MB

05 Recommender Systems/006 Exercise Improve the recommenders results.mp445.85MB

05 Recommender Systems/004 Activity Improving the Results of Movie Similarities.mp443.98MB

05 Recommender Systems/001 User-Based Collaborative Filtering.mp436.81MB

05 Recommender Systems/002 Item-Based Collaborative Filtering.mp433.56MB

06 More Data Mining and Machine Learning Techniques/006 Reinforcement Learning.mp463.56MB

06 More Data Mining and Machine Learning Techniques/002 Activity Using KNN to predict a rating for a movie.mp459.21MB

06 More Data Mining and Machine Learning Techniques/005 Data Warehousing Overview ETL and ELT.mp454.11MB

06 More Data Mining and Machine Learning Techniques/004 Activity PCA Example with the Iris data set.mp453.31MB

06 More Data Mining and Machine Learning Techniques/003 Dimensionality Reduction Principal Component Analysis.mp435.67MB

06 More Data Mining and Machine Learning Techniques/001 K-Nearest-Neighbors Concepts.mp419.9MB

07 Dealing with Real-World Data/004 Activity Cleaning web log data.mp460.16MB

07 Dealing with Real-World Data/002 Activity K-Fold Cross-Validation to avoid overfitting.mp445.87MB

07 Dealing with Real-World Data/006 Activity Detecting outliers.mp439.04MB

07 Dealing with Real-World Data/003 Data Cleaning and Normalization.mp431.9MB

07 Dealing with Real-World Data/001 BiasVariance Tradeoff.mp431.23MB

07 Dealing with Real-World Data/005 Normalizing numerical data.mp419.02MB

08 Apache Spark Machine Learning on Big Data/006 Activity Decision Trees in Spark.mp488.24MB

08 Apache Spark Machine Learning on Big Data/002 Activity Installing Spark - Part 2.mp481.68MB

08 Apache Spark Machine Learning on Big Data/007 Activity K-Means Clustering in Spark.mp462.85MB

08 Apache Spark Machine Learning on Big Data/009 Activity Searching Wikipedia with Spark.mp459.76MB

08 Apache Spark Machine Learning on Big Data/004 Spark and the Resilient Distributed Dataset RDD.mp436.41MB

08 Apache Spark Machine Learning on Big Data/003 Spark Introduction.mp432.46MB

08 Apache Spark Machine Learning on Big Data/008 TF IDF.mp432.2MB

08 Apache Spark Machine Learning on Big Data/005 Introducing MLLib.mp426.27MB

09 Experimental Design/005 AB Test Gotchas.mp443.78MB

09 Experimental Design/001 AB Testing Concepts.mp442.69MB

09 Experimental Design/003 Activity Hands-on With T-Tests.mp440.06MB

09 Experimental Design/002 T-Tests and P-Values.mp430.11MB

09 Experimental Design/004 Determining How Long to Run an Experiment.mp416.68MB

10 You made it/001 More to Explore.mp445.14MB

10 You made it/002 Bonus Lecture Discounts on Focused MapReduce and Spark Courses..mp433.44MB