17 OCT 2024 - Welcome Back to TorrentFunk! Get your pirate hat back out. Streaming is dying and torrents are the new trend. Account Registration works again and so do Torrent Uploads. We invite you all to start uploading torrents again!
TORRENT DETAILS
[FreeCoursesOnline.Me] [Packt] Hands-On Machine Learning With Scala And Spark [FCO]
TORRENT SUMMARY
Status:
All the torrents in this section have been verified by our verification system
Implement machine learning algorithms and evaluate how well they perform with the Scala programming language
Video Details
ISBN 9781789342468
Course Length 1 hours 41 minutes
Table of Contents
• ADVANCED TEXT PROCESSING IN SPARK AND BUILDING A CLASSIFICATION MODEL
• BUILDING A REGRESSION MODEL WITH SPARK
• BUILDING A CLUSTERING MODEL WITH SPARK
• DIMENSIONALITY REDUCTIONS AND RECOMMENDATION ENGINES
• DEEP LEARNING WITH SPARK
Video Description
Programmers face multiple challenges while implementing ML; dealing with unstructured data and picking the proper ML model are among the hardest.
In this course we will go through day-to-day challenges that programmers face when implementing ML pipelines and consider different approaches and models to solve complex problems.
You will learn about the most effective machine learning techniques and implement them in your favor. You will implement algorithms in practical hands-on projects, building data models and understanding how they work by using different types of algorithm.
Each section of the course deals with a specific machine learning problem and analysis and gives you insights by using real-world datasets.
By the end of this course, you will be able to take huge datasets, extract features from it, and apply a machine learning model that is well suited to your problem.
The code bundle for the course is available at: https://github.com/PacktPublishing/Hands-On-Machine-Learning-with-Scala-...
Style and Approach
This is a step-by-step and fast-paced guide that will help you learn how to create a ML model using the Apache Spark ML toolkit. With this practical approach, you will take your skills to the next level and will be able to create ML pipelines effectively.
What You Will Learn
• Extract features from data
• Write Scala code implementing ML algorithms for prediction and clustering
• Analyze the structure of datasets with exploratory data analysis techniques using Scala.
• Get to grips with the most popular machine learning algorithms used in the areas of regression, classification, clustering, dimensionality reduction, PCA, and neuralnetworks.
• Use the power of MLlib libraries to implement machine learning with Spark
• Using GMM to reason about time series data
• Work with the k-means and Naive Bayes algorithms and their methods and implement them in Scala with real datasets
Authors
Tomasz Lelek
Tomasz Lelek is a Software Engineer, programming mostly in Java and Scala. He has been working with the Spark and ML APIs for the past 5 years with production experience in processing petabytes of data.
He is passionate about nearly everything associated with software development and believes that we should always try to consider different solutions and approaches before solving a problem. Recently he was a speaker at conferences in Poland, Confitura and JDD (Java Developers Day), and at Krakow Scala User Group. He has also conducted a live coding session at Geecon Conference.
He is a co-founder of www.initlearn.com, an e-learning platform that was built with the Java language.
For More Udemy Free Courses >>> http://www.freetutorials.eu
For more Lynda and other Courses >>> https://www.freecoursesonline.me/
Our Forum for discussion >>> https://discuss.freetutorials.eu/
VISITOR COMMENTS (0 )
FILE LIST
Filename
Size
01.Advanced Text Processing in Spark and Building a Classification Model/0101.The Course Overview.mp4
19.2 MB
01.Advanced Text Processing in Spark and Building a Classification Model/0102.Analyzing Text Input Data.mp4
18.9 MB
01.Advanced Text Processing in Spark and Building a Classification Model/0103.Feature Generation from Text – Count Vectorizer, TFIDF, LDA.mp4
14.1 MB
01.Advanced Text Processing in Spark and Building a Classification Model/0104.Extracting Features from Data – Transforming Text into Vector of Numbers.mp4
22.7 MB
01.Advanced Text Processing in Spark and Building a Classification Model/0105.Bag-of-Words and Skip Gram.mp4
8.4 MB
01.Advanced Text Processing in Spark and Building a Classification Model/0106.Training Classification Models – Implementing Word2Vect Using Apache Spark.mp4
16.3 MB
02.Building a Regression Model with Spark/0201.Logistic Regression Explanation.mp4
8.6 MB
02.Building a Regression Model with Spark/0202.Writing a Logistic Regression Model Per Author in Apache Spark.mp4
8.6 MB
02.Building a Regression Model with Spark/0203.Training Regression Model.mp4
15.3 MB
02.Building a Regression Model with Spark/0204.Key Concepts, Machine Learning Pipelines, and Operations.mp4
10.4 MB
02.Building a Regression Model with Spark/0205.Learn How to Validate Models Using Cross-Validation.mp4
18.6 MB
03.Building a Clustering Model with Spark/0301.Analyzing Time of Post Using Clustering – (GMM Explanation).mp4
6.1 MB
03.Building a Clustering Model with Spark/0302.Implementing GMM in Apache Spark.mp4
31.5 MB
03.Building a Clustering Model with Spark/0303.K-Means Clustering Explanation and Use Cases.mp4
4.1 MB
03.Building a Clustering Model with Spark/0304.Implementing K-Means Clustering in Apache Spark.mp4
18.2 MB
03.Building a Clustering Model with Spark/0305.Measure Accuracy Using Area Under ROC.mp4
12.6 MB
04.Dimensionality Reductions and Recommendation Engines/0401.Dimensionality Reduction Using Singular Value Decomposition (SVD).mp4
14.1 MB
04.Dimensionality Reductions and Recommendation Engines/0402.Building Recommendation Engine in Spark Using Collaborative Filtering.mp4
18.2 MB
04.Dimensionality Reductions and Recommendation Engines/0403.Using Recommendation Engine to Get Top Recommendations.mp4
26.3 MB
04.Dimensionality Reductions and Recommendation Engines/0404.Dense and Sparse Vectors.mp4
13.7 MB
04.Dimensionality Reductions and Recommendation Engines/0405.LabeledPoints, Rating, and Other Data Types.mp4
10.5 MB
05.Deep Learning with Spark/0501.The Spark versus Deep Learning Use Case.mp4
7.7 MB
05.Deep Learning with Spark/0502.Spark for Parallelizing Deep Learning Evaluation.mp4
15.3 MB
05.Deep Learning with Spark/0503.Deep Learning As a Feature Generator for Existing Spark ML Algorithms.mp4
11.5 MB
05.Deep Learning with Spark/0504.SparkDeep Learning Made Simple.mp4
![[FreeCoursesOnline.Me] [Packt] Hands-On Machine Learning with Scala and Spark [FCO]](https://f.t0r.site/cover/18958377.webp)
