Spenser Confidential 2020 greys anatomy S16E19 Westworld S03E02 Keeping Up with the Kardashians S18E01 star trek picard legacies Station 19 ddr chicago fire s08e18 Last Man Standing S08E16 xxx Law and Order SVU S21E17 rq.mp4 A Million Little Things S02E19 Legacies S02E16 The Banker 2020 ozark Birds of Prey (and the Fantabulous Emancipation of One Harley Quinn) 2020 knives out 2019 hindi Bloodshot 2020 The Hunt 2020 westworld Star Trek Picard S01E09 picard s01e10 Superstore S05E19 Ozark S03E01 The Invisible Man 2020 evo brooklyn fantasy island 2020 The Gentlemen 2019 bad boys for life Frozen II 2019 Onward 2020 Brooklyn Nine-Nine S07E09 Greys Anatomy Jumanji The Next Level 2019 the sinner Star Trek Picard S01E10 ettv The call of the wild 1917 2019 Bad Boys for Life 2020 brooklyn nine nine Deputy S01E13 underwater Underwater 2020 Dolittle 2020 The Sinner S03E08 Chicago P.D. S07E18 etrg SEAL Team S03E16 S.W.A.T. S03E17 clone wars the gentlemen 2020 Vivarium  picard Sonic the Hedgehog 2020 Brooklyn Nine Nine S07E09 the way back 2020 The Call of the Wild 2020 bad boys etmovies yts the walking dead Contagion 2011 Star Wars The Rise of Skywalker 2019 A Quiet Place Part II 2020 ethd bloodshot station 19 s03e10 
ETTV Recommended TV Shows
Deputy.S01E13.WEB.x264-XLF[ettv] torrent
MacGyver.2016.S04E07.HDTV.x264-SVA[ettv] torrent
The.Walking.Dead.S10E14.WEB.H264-XLF[ettv] torrent
Hawaii.Five-0.2010.S10E21.HDTV.x264-SVA[ettv] torrent
Strike.Back.S08E07.WEB.H264-XLF[ettv] torrent
WWE Smackdown 2020 03 27 HDTV x264-Star [TJET] torrent

ETTV Recommended SD
The Call of the Wild.2020.HDRip.XviD.AC3-EVO torrent
Resistance.2020.HDRip.XviD.AC3-EVO torrent
Homeward.2020.BRRip.XviD.AC3-EVO torrent
What.Love.Looks.Like.2020.HDRip.XviD.AC3-EVO torrent

ETTV Recommended HD
Frontier.2020.1080p.AMZN.WEB-DL.DDP2.0.H264-CMRG[EtHD] torrent
Downhill.2020.1080p.AMZN.WEB-DL.DDP5.1.H.264-TOMMY[EtHD] torrent
What.Love.Looks.Like.2020.1080p.AMZN.WEB-DL.DDP2.0.H264-CMRG[EtHD] torrent
Haunt.2019.1080p.BluRay.x264-GETiT[EtHD] torrent

ETTV Recommended UHD
Star.Wars.Episode.IX.The.Rise.of.Skywalker.2019.4K.HDR.2160p.BDRip Ita Eng x265-NAHOM torrent
Transformers.Age.of.Extinction.2014.BDRip.2160p.UHD.HDR.TrueHD.ETRG torrent
Transformers.The.Last.Knight.2017.BDRip.2160p.UHD.HDR.TrueHD.ETRG torrent
Lady.and.the.Tramp 2019 4K.HDR.2160p.WEBDL Ita Eng x265-NAHOM torrent

ETTV Recommended Cam
My Spy 2020 HDCAM x264 AC3-ETRG torrent
The Hunt 2020 HDCAM x264 AC3-ETRG torrent
The Burnt Orange Heresy 2020 720p HDCAM-C1NEM4 torrent
Fantasy Island 2020 UNRATED HDTS x264 AC3-ETRG torrent

ETTV Recommended Foreign
Maska.2020.1080p.NF.WEB-DL.HIN-Eng.DD+5.1.Atmos.x264-Telly torrent
Jawaani.Jaaneman.2020.1080p.AMZN.WEB-DL.DD+5.1.x264-Telly torrent
Bonus.2020.1080p.AMZN.WEB-DL.DD+5.1.x264-Telly torrent
Underwater (2020) HDRip 720p [Hindi-Dub] Dual-Audio x264 - 1XCinema torrent


Download Torrent "Pluralsight | Creating Machine Learning Models [FCO]"

Download Torrent (Magnet)
Seeds: 281
Leechers: 51
Completed: 2,454 
Last Checked: 24-03-2020 16:33:52


Details
Title:Pluralsight | Creating Machine Learning Models [FCO]
Description:
Lynda and other Courses >>> https://www.freecoursesonline.me/
For Developer Tools & Apps >>> https://ftuapps.com/
Forum for discussion >>> https://1hack.us/




Created by: Janani Ravi
Language: English
Updated: Oct 29, 2019
Duration: 2h 44m
Course Source: https://www.pluralsight.com/courses/creating-machine-learning-models

About

This course covers the important types of machine learning algorithms, solution techniques based on the specifics of the problem you are trying to solve, as well as the classic machine learning workflow.

Description

As Machine Learning explodes in popularity, it is becoming ever more important to know precisely how to frame a machine learning model in a manner appropriate to the problem we are trying to solve, and the data that we have available.

In this course, Creating Machine Learning Models you will gain the ability to choose the right type of model for your problem, then build that model, and evaluate its performance.

First, you will learn how rule-based and ML-based systems differ and their strengths and weaknesses and how supervised and unsupervised learning models differ from each other.

Next, you will discover how to implement a range of techniques to solve the supervised learning problems of classification and regression. You will gain an intuitive understanding of the the model algorithms you can use for classification and regression. Finally, you will round out your knowledge by building clustering models using a couple of different algorithms, and validating the results.

When you’re finished with this course, you will have the skills and knowledge to identify the correct machine learning problem setup, and the appropriate solution and evaluation techniques for your use-case.

Level

• Intermediate

About Author

A problem solver at heart, Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework.




Category:Tutorials > Tutorials
Lang:English  English
Total Size:391 MB
Info Hash:85a166d9dde8bd9d31faf588af0cf89a0e110fc3
Added By:Prom3th3uS
Date Added:24-03-2020 16:33:44

  

Files

File List: 
 File Size
0. Websites you may like/0. (1Hack.Us) Premium Tutorials-Guides-Articles & Community based Forum.url377.00 B
0. Websites you may like/1. (FreeCoursesOnline.Me) Download Udacity, Masterclass, Lynda, PHLearn, Pluralsight Free.url286.00 B
0. Websites you may like/2. (NulledPremium.com) Download E-Learning, E-Books, Audio-Books, & more.etc.url163.00 B
0. Websites you may like/3. (FTUApps.com) Download Cracked Developers Applications For Free.url239.00 B
0. Websites you may like/How you can help our Group!.txt208.00 B
01.Course Overview/01.01.Course Overview.mp410 MB
02.Understanding Approaches to Machine Learning/02.01.Module Overview.mp47 MB
02.Understanding Approaches to Machine Learning/02.02.Prerequisites and Course Outline.mp45 MB
02.Understanding Approaches to Machine Learning/02.03.Rule-based vs. ML-based Learning.mp414 MB
02.Understanding Approaches to Machine Learning/02.04.Traditional ML vs. Representation ML.mp47 MB
02.Understanding Approaches to Machine Learning/02.05.The Machine Learning Workflow.mp46 MB
02.Understanding Approaches to Machine Learning/02.06.Choosing the Right Model Based on Data.mp410 MB
02.Understanding Approaches to Machine Learning/02.07.Supervised vs. Unsupervised Learning.mp49 MB
02.Understanding Approaches to Machine Learning/02.08.Transfer Learning, Cold Start ML and Warm Start ML.mp410 MB
02.Understanding Approaches to Machine Learning/02.09.Popular Machine Learning Frameworks.mp47 MB
02.Understanding Approaches to Machine Learning/02.10.Demo Getting Started with scikit-learn.mp44 MB
02.Understanding Approaches to Machine Learning/02.11.Module Summary.mp43 MB
03.Understanding and Implementing Regression Models/03.01.Module Overview.mp42 MB
03.Understanding and Implementing Regression Models/03.02.Building and Evaluating Regression Models.mp49 MB
03.Understanding and Implementing Regression Models/03.03.Demo Linear Regression Using Numeric Features.mp418 MB
03.Understanding and Implementing Regression Models/03.04.Demo Exploring Regression Data.mp410 MB
03.Understanding and Implementing Regression Models/03.05.Demo Preprocessing Numeric and Categorical Data and Fitting a Regression Model.mp410 MB
03.Understanding and Implementing Regression Models/03.06.Choosing Regression Algorithms.mp45 MB
03.Understanding and Implementing Regression Models/03.07.Regularized Regression Models Lasso, Ridge, and Elastic Net.mp47 MB
03.Understanding and Implementing Regression Models/03.08.Stochastic Gradient Descent.mp44 MB
03.Understanding and Implementing Regression Models/03.09.Demo Multiple Types of Regression.mp412 MB
03.Understanding and Implementing Regression Models/03.10.Module Summary.mp43 MB
04.Understanding and Implementing Classification Models/04.01.Module Overview.mp42 MB
04.Understanding and Implementing Classification Models/04.02.Types of Classifiers.mp48 MB
04.Understanding and Implementing Classification Models/04.03.Understanding Logistic Regression Intuitively.mp410 MB
04.Understanding and Implementing Classification Models/04.04.Demo Building and Training a Binary Classification Model.mp414 MB
04.Understanding and Implementing Classification Models/04.05.Understanding Support Vector and Nearest Neighbors Classification.mp47 MB
04.Understanding and Implementing Classification Models/04.06.Understanding Decision Tree and Naive Bayes Classification.mp410 MB
04.Understanding and Implementing Classification Models/04.07.Demo Building Classification Models Using Multiple Techniques.mp415 MB
04.Understanding and Implementing Classification Models/04.08.Demo Using Warm Start with an Ensemble Classifier.mp47 MB
04.Understanding and Implementing Classification Models/04.09.Demo Performing Multiclass Classification on Text Data.mp415 MB
04.Understanding and Implementing Classification Models/04.10.Module Summary.mp42 MB
05.Understanding and Implementing Clustering Model/05.01.Module Overview.mp42 MB
05.Understanding and Implementing Clustering Model/05.02.Clustering as an Unsupervised Learning Technique.mp48 MB
05.Understanding and Implementing Clustering Model/05.03.Choosing Clustering Algorithms.mp47 MB
05.Understanding and Implementing Clustering Model/05.04.Categorizing Clustering Algorithms.mp46 MB
05.Understanding and Implementing Clustering Model/05.05.K-means Clustering.mp45 MB
05.Understanding and Implementing Clustering Model/05.06.Hierarchical Clustering.mp47 MB
05.Understanding and Implementing Clustering Model/05.07.Demo Performing K-means Clustering on Unlabeled Data.mp412 MB
05.Understanding and Implementing Clustering Model/05.08.Demo Clustering Using Labeled Data.mp418 MB
05.Understanding and Implementing Clustering Model/05.09.Demo Agglomerative Clustering.mp449 MB
05.Understanding and Implementing Clustering Model/05.10.Summary and Further Study.mp47 MB
Exercise_file.zip8 MB



Comments

There are currently no comments. Be the first one to write something !