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种子名称： Building Machine Learning Models in Spark 2
文件类型： 视频
文件数目： 54个文件
文件大小： 397.87 MB
收录时间： 2019-5-22 20:18
已经下载： 3次
资源热度： 108
最近下载： 2024-10-19 20:24

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Building Machine Learning Models in Spark 2.torrent

02.Machine Learning Packages spark.mllib vs. spark.ml/0210.Demo Wine Classification Using Decision Trees in spark.mllib.mp419.99MB

02.Machine Learning Packages spark.mllib vs. spark.ml/0201.Module Overview.mp42.59MB

02.Machine Learning Packages spark.mllib vs. spark.ml/0202.Prerequisites and Course Overview.mp44.55MB

02.Machine Learning Packages spark.mllib vs. spark.ml/0203.RDDs The Building Blocks of Spark.mp45.63MB

02.Machine Learning Packages spark.mllib vs. spark.ml/0204.DataFrames in Spark 2.mp42.62MB

02.Machine Learning Packages spark.mllib vs. spark.ml/0205.Demo Spark 2 Installation and Working with Jupyter Notebooks.mp49.19MB

02.Machine Learning Packages spark.mllib vs. spark.ml/0206.spark.mllib vs. spark.ml.mp46.5MB

02.Machine Learning Packages spark.mllib vs. spark.ml/0207.Introducing Decision Trees.mp47.43MB

02.Machine Learning Packages spark.mllib vs. spark.ml/0208.Gini Impurity and Pros and Cons of Decision Trees.mp48.45MB

02.Machine Learning Packages spark.mllib vs. spark.ml/0209.Demo Basic Project Setup.mp45.23MB

01.Course Overview/0101.Course Overview.mp44.89MB

02.Machine Learning Packages spark.mllib vs. spark.ml/0211.Demo Working with the LIBSVM Data Format.mp42.68MB

02.Machine Learning Packages spark.mllib vs. spark.ml/0212.Demo Decision Trees Using the LIBSVM Data Format.mp415.21MB

03.Building Classification and Regression Models in Spark ML/0301.Module Overview.mp42.46MB

03.Building Classification and Regression Models in Spark ML/0302.ML Pipelines, Estimators, and Transformers.mp48.69MB

03.Building Classification and Regression Models in Spark ML/0303.Training and Prediction Pipeline Stages.mp44.83MB

03.Building Classification and Regression Models in Spark ML/0304.Feature Engineering.mp43.24MB

03.Building Classification and Regression Models in Spark ML/0305.Feature Extractors.mp45.8MB

03.Building Classification and Regression Models in Spark ML/0306.Feature Transformers.mp44.91MB

03.Building Classification and Regression Models in Spark ML/0307.Feature Selectors and Locality Sensitive Hashing.mp41.15MB

03.Building Classification and Regression Models in Spark ML/0308.The Confusion Matrix Accuracy, Precision, Recall, F1 Score.mp47.42MB

03.Building Classification and Regression Models in Spark ML/0309.Demo Wine Classification Using Decision Trees in Spark ML.mp47.49MB

03.Building Classification and Regression Models in Spark ML/0310.Demo Converting Categorical Data to Numeric Values.mp44.72MB

03.Building Classification and Regression Models in Spark ML/0311.Demo The Decision Tree Classifier.mp46.13MB

03.Building Classification and Regression Models in Spark ML/0312.Random Forests.mp45.01MB

03.Building Classification and Regression Models in Spark ML/0313.Demo Income Classification Using Random Forests.mp410.7MB

03.Building Classification and Regression Models in Spark ML/0314.Demo Using ML Pipelines.mp415.45MB

03.Building Classification and Regression Models in Spark ML/0315.Demo Predictions Using the Random Forest .mp44.93MB

03.Building Classification and Regression Models in Spark ML/0316.Introducing Regularized Regression Models to Prevent Overfitting.mp47.43MB

03.Building Classification and Regression Models in Spark ML/0317.Lasso and Ridge Regression.mp44.01MB

03.Building Classification and Regression Models in Spark ML/0318.Demo Linear Regression with the Elastic Net Param.mp48.97MB

03.Building Classification and Regression Models in Spark ML/0319.Demo Predictions Using the Regression Model.mp47.06MB

03.Building Classification and Regression Models in Spark ML/0320.Demo Hyperparameter Tuning.mp48.72MB

04.Implementing Clustering and Dimensionality Reduction in Spark ML/0401.Module Overview.mp42.88MB

04.Implementing Clustering and Dimensionality Reduction in Spark ML/0402.Supervised and Unsupervised Learning Techniques.mp48.3MB

04.Implementing Clustering and Dimensionality Reduction in Spark ML/0403.Clustering Objectives.mp45.97MB

04.Implementing Clustering and Dimensionality Reduction in Spark ML/0404.Visualizing K-means Clustering.mp43.01MB

04.Implementing Clustering and Dimensionality Reduction in Spark ML/0405.Number of Clusters as a Hyperparameter The Elbow and Silhouette Method.mp410.22MB

04.Implementing Clustering and Dimensionality Reduction in Spark ML/0406.Demo K-means Clustering on the Titanic Dataset.mp413.56MB

04.Implementing Clustering and Dimensionality Reduction in Spark ML/0407.Demo Exploring Clusters.mp418.5MB

04.Implementing Clustering and Dimensionality Reduction in Spark ML/0408.Principal Component Analysis Intuition.mp46.84MB

04.Implementing Clustering and Dimensionality Reduction in Spark ML/0409.Demo Regression Model Without PCA.mp415.32MB

04.Implementing Clustering and Dimensionality Reduction in Spark ML/0410.Demo Performing Regression on Principal Components.mp414.97MB

05.Building Recommendation Systems in Spark ML/0501.Module Overview.mp41.79MB

05.Building Recommendation Systems in Spark ML/0502.Content-based and Collaborative Filtering.mp48MB

05.Building Recommendation Systems in Spark ML/0503.Estimating the Ratings Matrix.mp410.41MB

05.Building Recommendation Systems in Spark ML/0504.The Alternating Least Squares Method.mp42.69MB

05.Building Recommendation Systems in Spark ML/0505.Explicit and Implicit Ratings.mp49.32MB

05.Building Recommendation Systems in Spark ML/0506.Cold Start Strategies and Compute Intensity.mp42.67MB

05.Building Recommendation Systems in Spark ML/0507.Demo Building a Recommendation System Using Explicit Ratings.mp48.35MB

05.Building Recommendation Systems in Spark ML/0508.Demo Getting Movie Recommendations for Specific Users.mp410.86MB

05.Building Recommendation Systems in Spark ML/0509.Demo Building a Recommendation System Using Implicit Ratings.mp48.53MB

05.Building Recommendation Systems in Spark ML/0510.Demo Getting Artist Recommendations for Specific Users.mp48.66MB

05.Building Recommendation Systems in Spark ML/0511.Summary and Further Study.mp42.94MB