Pluralsight - Building Machine Learning Models in Spark 2

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Building Machine Learning Models in Spark 2 01.Course Overview
  • 0101.Course Overview.mp4 (4.9 MB)
02.Machine Learning Packages spark.mllib vs. spark.ml
  • 0201.Module Overview.mp4 (2.6 MB)
  • 0202.Prerequisites and Course Overview.mp4 (4.6 MB)
  • 0203.RDDs The Building Blocks of Spark.mp4 (5.6 MB)
  • 0204.DataFrames in Spark 2.mp4 (2.6 MB)
  • 0205.Demo Spark 2 Installation and Working with Jupyter Notebooks.mp4 (9.2 MB)
  • 0206.spark.mllib vs. spark.ml.mp4 (6.5 MB)
  • 0207.Introducing Decision Trees.mp4 (7.4 MB)
  • 0208.Gini Impurity and Pros and Cons of Decision Trees.mp4 (8.4 MB)
  • 0209.Demo Basic Project Setup.mp4 (5.2 MB)
  • 0210.Demo Wine Classification Using Decision Trees in spark.mllib.mp4 (20.0 MB)
  • 0211.Demo Working with the LIBSVM Data Format.mp4 (2.7 MB)
  • 0212.Demo Decision Trees Using the LIBSVM Data Format.mp4 (15.2 MB)
03.Building Classification and Regression Models in Spark ML
  • 0301.Module Overview.mp4 (2.5 MB)
  • 0302.ML Pipelines, Estimators, and Transformers.mp4 (8.7 MB)
  • 0303.Training and Prediction Pipeline Stages.mp4 (4.8 MB)
  • 0304.Feature Engineering.mp4 (3.2 MB)
  • 0305.Feature Extractors.mp4 (5.8 MB)
  • 0306.Feature Transformers.mp4 (4.9 MB)
  • 0307.Feature Selectors and Locality Sensitive Hashing.mp4 (1.1 MB)
  • 0308.The Confusion Matrix Accuracy, Precision, Recall, F1 Score.mp4 (7.4 MB)
  • 0309.Demo Wine Classification Using Decision Trees in Spark ML.mp4 (7.5 MB)
  • 0310.Demo Converting Categorical Data to Numeric Values.mp4 (4.7 MB)
  • 0311.Demo The Decision Tree Classifier.mp4 (6.1 MB)
  • 0312.Random Forests.mp4 (5.0 MB)
  • 0313.Demo Income Classification Using Random Forests.mp4 (10.7 MB)
  • 0314.Demo Using ML Pipelines.mp4 (15.4 MB)
  • 0315.Demo Predictions Using the Random Forest .mp4 (4.9 MB)
  • 0316.Introducing Regularized Regression Models to Prevent Overfitting.mp4 (7.4 MB)
  • 0317.Lasso and Ridge Regression.mp4 (4.0 MB)
  • 0318.Demo Linear Regression with the Elastic Net Param.mp4 (9.0 MB)
  • 0319.Demo Predictions Using the Regression Model.mp4 (7.1 MB)
  • 0320.Demo Hyperparameter Tuning.mp4 (8.7 MB)
04.Implementing Clustering and Dimensionality Reduction in Spark ML
  • 0401.Module Overview.mp4 (2.9 MB)
  • 0402.Supervised and Unsupervised Learning Techniques.mp4 (8.3 MB)
  • 0403.Clustering Objectives.mp4 (6.0 MB)
  • 0404.Visualizing K-means Clustering.mp4 (3.0 MB)
  • 0405.Number of Clusters as a Hyperparameter The Elbow and Silhouette Method.mp4 (10.2 MB)
  • 0406.Demo K-means Clustering on the Titanic Dataset.mp4 (13.6 MB)
  • 0407.Demo Exploring Clusters.mp4 (18.5 MB)
  • 0408.Principal Component Analysis Intuition.mp4 (6.8 MB)
  • 0409.Demo Regression Model Without PCA.mp4 (15.3 MB)
  • 0410.Demo Performing Regression on Principal Components.mp4 (15.0 MB)
05.Building Recommendation Systems in Spark ML
  • 0501.Module Overview.mp4 (1.8 MB)
  • 0502.Content-based and Collaborative Filtering.mp4 (8.0 MB)
  • 0503.Estimating the Ratings Matrix.mp4 (10.4 MB)
  • 0504.The Alternating Least Squares Method.mp4 (2.7 MB)
  • 0505.Explicit and Implicit Ratings.mp4 (9.3 MB)
  • 0506.Cold Start Strategies and Compute Intensity.mp4 (2.7 MB)
  • 0507.Demo Building a Recommendation System Using Explicit Ratings.mp4 (8.4 MB)
  • 0508.Demo Getting Movie Recommendations for Specific Users.mp4 (10.9 MB)
  • 0509.Demo Building a Recommendation System Using Implicit Ratings.mp4 (8.5 MB)
  • 0510.Demo Getting Artist Recommendations for Specific Users.mp4 (8.7 MB)
  • 0511.Summary and Further Study.mp4 (2.9 MB)
Exercise Files
  • spark-2-building-machine-learning-models.zip (7.7 MB)

Description

Code:

Title: Building Machine Learning Models in Spark 2
Publisher: Pluralsight
Size: 405 MB
Type: N/A
URL: https://www.pluralsight.com/courses/spark-2-building-machine-learning-models
Author: Janani Ravi
Duration: 3h 27m
Skill: Intermediate



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Pluralsight - Building Machine Learning Models in Spark 2

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Pluralsight - Building Machine Learning Models in Spark 2

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