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TORRENT DETAILS

[FreeCoursesOnline.Me] [Packt] Python And Data Science A Practical Guide [FCO]

TORRENT SUMMARY

	Status:	All the torrents in this section have been verified by our verification system
Category:	Other
Infohash	188478f4e80a7b36b73c15e29c2a825c7ac79a6b
Size:	3.1 GB in 78 files
Release Date(s):	Torrent Release: 06-04-2019 by user
Swarm:	0 Seeds & 0 Peers
Vote:	No votes yet.

DESCRIPTION

By: Eduonix, Michael Mustaine

Released: Friday, March 29, 2019 [New Release!]

Torrent Contains: 80 Files, 15 Folders

Course Source: https://www.packtpub.com/application-development/python-and-data-science-practical-guide-video

Learn Data Science and Python to do Web Scraping, Data Analysis, Data Visualization, Machine Learning, Deep Learning...

Video Details

ISBN 9781838553012

Course Length 13 hours 9 minutes

Table of Contents

• INTRODUCTION

• ENVIRONMENT

• INTEGERS AND STRINGS

• IF STATEMENTS AND BASIC PROGRAMMING LOGIC

• LISTS, TUPLES, DICTIONARIES AND FOR/WHILE LOOPS

• FUNCTIONS AND PACKAGES

• PANDAS AND DATA FRAMES

• VISUALIZATION - SCATTER PLOTS, BAR PLOTS

• SCRAPING THE WEB WITH PYTHON

• BASICS OF NATURAL LANGUAGE PROCESSING (NLP)

• INTRODUCTION TO MACHINE LEARNING

• OPTIONAL CLASSES

• PROJECT #1 - ANALYZE AND VISUALIZE DATA ON KAGGLE

• PROJECT #2 - NATURAL LANGUAGE PROCESSING

• PROJECT #3 - CREATE A SIMPLE SUPPORT VECTOR MACHINE

Video Description

This course is designed to teach you the basics of Python and Data Science in a practical way, so that you can acquire, test, and master your Python skills gradually.

You’ll see that you'll learn all these things with Python:

• Using Variables & Strings

• Using Booleans & Logical Operators

• Using Functions & Packages

• Using Lists, Tuples and Dictionaries

• Using For & While Loops

• Using Panda & Data Frames

• Doing Data Visualization

• Scraping Web Data

• Doing some basic Natural Language Processing (NLP)

• Basics of Machine Learning & Deep Learning

And much more to come.

Style and Approach

This course is designed in a practical way to teach you the basics of Python and Data Science. A complete course packed with step-by-step instructions, working examples, and helpful advice. This course is clearly divided into small parts that will help you understand each part individually and help you learn at your own pace.

What You Will Learn

• How to set up your Python environment

• How to manipulate String & Variables with Python

• How to use Booleans & Logical Operators with Python

• How to use Functions & Packages with Python

• How to use Pandas & Data Frames with Python

• How to perform Data Visualization with Python

• How to do Web Scraping with Python

• The Basics of Natural Language Processing (NLP)

• The Basics of Deep Learning & Reinforcement Learning

Authors

Eduonix

Eduonix Learning Solutions creates and distributes high-quality technology training content. Their team of industry professionals have been training manpower for more than a decade. They aim to teach technology the way it is used in industry and the professional world. They have a professional team of trainers for technologies ranging from mobility, web to enterprise and database and server administration

Michael Mustaine

Michael Mustaine is a polymath with academic and professional experience in psychology and data science. He has created innovative human-centric analysis for user segmentation, feature selection, machine learning, and key performance metric generation specialized to individual client needs. Recent clients include: cryptocurrency hedgefunds, not-for-profit data journalists, and universities. He provide interpretable evaluations of complex behaviour with a degree of innovation that only comes from being a trailblazer in the field.

For More Udemy Free Courses >>> https://ftuforum.com/

For more Lynda and other Courses >>> https://www.freecoursesonline.me/

Our Forum for discussion >>> https://discuss.ftuforum.com/

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FILE LIST

Filename		Size
	01.Introduction/0101.Introduction.mp4	16.8 MB
	02.Environment/0201.Introduction to data science.mp4	235 MB
	02.Environment/0202.Installing dependencies.mp4	39.3 MB
	02.Environment/0203.Real world examples.mp4	30.1 MB
	02.Environment/0204.Using Anaconda and Jupyter notebooks.mp4	55.2 MB
	03.Integers and Strings/0301.Introduction to variables.mp4	58.6 MB
	03.Integers and Strings/0302.Integers, floats, and math operators.mp4	53.8 MB
	03.Integers and Strings/0303.Strings and indexing part 1.mp4	38 MB
	03.Integers and Strings/0304.Strings and indexing part 2.mp4	32.9 MB
	03.Integers and Strings/0305.Using Modulo with Strings.mp4	32 MB
	03.Integers and Strings/0306.Problem.mp4	10.8 MB
	03.Integers and Strings/0307.Answer.mp4	26 MB
	04.If Statements and Basic Programming Logic/0401.Booleans and Comparison Operators.mp4	48.1 MB
	04.If Statements and Basic Programming Logic/0402.If Else Statements.mp4	38.7 MB
	04.If Statements and Basic Programming Logic/0403.Elif and Logic Operators.mp4	41.7 MB
	04.If Statements and Basic Programming Logic/0404.Try Except Statements.mp4	33.1 MB
	04.If Statements and Basic Programming Logic/0405.Finally Statements and Advance TryExcept Logic.mp4	32.4 MB
	04.If Statements and Basic Programming Logic/0406.Exception Types.mp4	51.2 MB
	04.If Statements and Basic Programming Logic/0407.Problem.mp4	7.7 MB
	04.If Statements and Basic Programming Logic/0408.Answer.mp4	25.1 MB
	05.Lists, Tuples, Dictionaries and ForWhile Loops/0501.Lists and tuples.mp4	71 MB
	05.Lists, Tuples, Dictionaries and ForWhile Loops/0502.Dictionaries.mp4	64 MB
	05.Lists, Tuples, Dictionaries and ForWhile Loops/0503.For loops.mp4	61.9 MB
	05.Lists, Tuples, Dictionaries and ForWhile Loops/0504.While loops.mp4	34.7 MB
	05.Lists, Tuples, Dictionaries and ForWhile Loops/0505.Loop logic.mp4	50.5 MB
	05.Lists, Tuples, Dictionaries and ForWhile Loops/0506.ListDictionary comprehensions.mp4	47.3 MB
	05.Lists, Tuples, Dictionaries and ForWhile Loops/0507.Problem.mp4	7.1 MB
	05.Lists, Tuples, Dictionaries and ForWhile Loops/0508.Answer.mp4	42.3 MB
	06.Functions and Packages/0601.Scripting in Python.mp4	50.3 MB
	06.Functions and Packages/0602.Functions.mp4	49.5 MB
	06.Functions and Packages/0603.Function parameters and scope.mp4	39.9 MB
	06.Functions and Packages/0604.Packages and pip.mp4	49 MB
	06.Functions and Packages/0605.Reading Files and the with statement.mp4	67 MB
	06.Functions and Packages/0606.Writing Out to Files.mp4	81 MB
	06.Functions and Packages/0607.Problem.mp4	8.8 MB
	06.Functions and Packages/0608.Answer.mp4	31.5 MB
	07.Pandas and Data Frames/0701.Pandas and data Frames.mp4	51.1 MB
	07.Pandas and Data Frames/0702.Pandas part 2.mp4	67 MB
	07.Pandas and Data Frames/0703.Introduction to statistics.mp4	52.1 MB
	07.Pandas and Data Frames/0704.Statistics part 2.mp4	40.7 MB
	07.Pandas and Data Frames/0705.Practical analysis.mp4	59.5 MB
	07.Pandas and Data Frames/0706.Problem.mp4	17.3 MB
	07.Pandas and Data Frames/0707.Answer.mp4	23.4 MB
	08.Visualization - Scatter Plots, Bar Plots/0801.Introduction to visualization.mp4	52.7 MB
	08.Visualization - Scatter Plots, Bar Plots/0802.Plotting and styling.mp4	55.9 MB
	08.Visualization - Scatter Plots, Bar Plots/0803.Scatter plots.mp4	50.5 MB
	08.Visualization - Scatter Plots, Bar Plots/0804.Bar Plots and standard deviation.mp4	53.3 MB
	08.Visualization - Scatter Plots, Bar Plots/0805.Problem.mp4	12.6 MB
	08.Visualization - Scatter Plots, Bar Plots/0806.Answer.mp4	50.2 MB
	09.Scraping the Web with Python/0901.Scraping and HTML.mp4	47.6 MB
	09.Scraping the Web with Python/0902.Building a simple crawler.mp4	47.3 MB
	09.Scraping the Web with Python/0903.Scraping data from HTML.mp4	57 MB
	09.Scraping the Web with Python/0904.Problem.mp4	11.6 MB
	09.Scraping the Web with Python/0905.Answer.mp4	36.3 MB
	10.Basics of Natural Language Processing (NLP)/1001.Introduction to NLP.mp4	51.8 MB
	10.Basics of Natural Language Processing (NLP)/1002.Basic NLP.mp4	64 MB
	10.Basics of Natural Language Processing (NLP)/1003.Introduction to sentiment analysis.mp4	74.3 MB
	10.Basics of Natural Language Processing (NLP)/1004.Problem.mp4	8.3 MB
	10.Basics of Natural Language Processing (NLP)/1005.Answer.mp4	33.2 MB
	11.Introduction to Machine Learning/1101.Introduction to machine learning.mp4	60.4 MB
	11.Introduction to Machine Learning/1102.Introduction to reinforcement learning.mp4	19.6 MB
	11.Introduction to Machine Learning/1103.Introduction to random forest modeling.mp4	64.4 MB
	11.Introduction to Machine Learning/1104.Introduction to deep learning.mp4	61.4 MB
	11.Introduction to Machine Learning/1105.Problem.mp4	24.1 MB
	11.Introduction to Machine Learning/1106.Answer.mp4	29.7 MB
	12.Optional Classes/1201.Python Style Guidelines.mp4	44.3 MB
	12.Optional Classes/1202.Navigating Directories and os Package.mp4	48.4 MB
	12.Optional Classes/1203.Creating a Class Type.mp4	45.7 MB
	13.Project #1 - Analyze and visualize data on Kaggle/1301.Project 1 - Analyze and visualize data on Kaggle.mp4	17.8 MB
	13.Project #1 - Analyze and visualize data on Kaggle/1302.Project 1 Answer.mp4	11.9 MB
	14.Project #2 - Natural language processing/1401.Project 2 - Natural language processing.mp4	7 MB
	14.Project #2 - Natural language processing/1402.Project 2 Answer.mp4	20.1 MB
	15.Project #3 - Create a simple support vector machine/1501.Project 3 - Create a simple support vector machine.mp4	19.6 MB
	15.Project #3 - Create a simple support vector machine/1502.Project 3 Answer.mp4	43.1 MB
	Discuss.FTUForum.com.html	31.9 KB
	FreeCoursesOnline.Me.html	108.3 KB
	FTUForum.com.html	100.4 KB
	How you can help Team-FTU.txt	235 B

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