10 JUL 2026 - Back up to full speed! Let's be honest: for the last few months, TorrentFunk was painfully slow. Pages crawled, searches dragged, and just loading the site tested everyone's patience. We hunted the problem down to our network and rebuilt it from the ground up — smarter caching, a much bigger and faster connection, and a lot of fine-tuning under the hood. The difference is night and day: the site now loads in a fraction of a second. No more waiting around. Thanks for sticking with us through the slow spell. Now go discover your funk!
TORRENT DETAILS
[NulledPremium.com] Statistics For Data Science
TORRENT SUMMARY
Status:
All the torrents in this section have been verified by our verification system
For More Ebooks Visit NulledPremium >>> NulledPremium.com
Book details File Size: 3.80 MB Format: epub Print Length: 288 pages Page Numbers Source ISBN: 1788290674 Publisher: Packt Publishing; 1 edition (November 17, 2017) Publication Date: November 17, 2017 Sold by: Amazon Digital Services LLC Language: English ASIN: B06Y2XX2LH
Get your statistics basics right before diving into the world of data science
Key Features
No need to take a degree in statistics, read this book and get a strong statistics base for data science and real-world programs; Implement statistics in data science tasks such as data cleaning, mining, and analysis Learn all about probability, statistics, numerical computations, and more with the help of R programs Book Description Data science is an ever-evolving field, which is growing in popularity at an exponential rate. Data science includes techniques and theories extracted from the fields of statistics; computer science, and, most importantly, machine learning, databases, data visualization, and so on.
This book takes you through an entire journey of statistics, from knowing very little to becoming comfortable in using various statistical methods for data science tasks. It starts off with simple statistics and then move on to statistical methods that are used in data science algorithms. The R programs for statistical computation are clearly explained along with logic. You will come across various mathematical concepts, such as variance, standard deviation, probability, matrix calculations, and more. You will learn only what is required to implement statistics in data science tasks such as data cleaning, mining, and analysis. You will learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks.
By the end of the book, you will be comfortable with performing various statistical computations for data science programmatically.
What you will learn
Analyze the transition from a data developer to a data scientist mindset Get acquainted with the R programs and the logic used for statistical computations Understand mathematical concepts such as variance, standard deviation, probability, matrix calculations, and more Learn to implement statistics in data science tasks such as data cleaning, mining, and analysis Learn the statistical techniques required to perform tasks such as linear regression, regularization, model assessment, boosting, SVMs, and working with neural networks Get comfortable with performing various statistical computations for data science programmatically Style and approach Step by step comprehensive guide with real world examples
Who This Book Is For This book is intended for those developers who are willing to enter the field of data science and are looking for concise information of statistics with the help of insightful programs and simple explanation. Some basic hands on R will be useful.
Table of Contents
Transitioning from Data Developer to Data Scientist Declaring the Objectives A Developer’s Approach to Data Cleaning Data Mining and the Database Developer Statistical Analysis for the Database Developer Database Progression to Database Regression Regularization for Database Improvement Database Development and Assessment Databases and Neural Networks Boosting your Database Database Classification using Support Vector Machines Database Structures and Machine Learning
VISITOR COMMENTS (0 )
FILE LIST
Filename
Size
Statistics for Data Science by James D. Miller.epub
3.8 MB
Websites you may like/How you can help Team-FTU.txt
![[NulledPremium.com] Statistics for Data Science](https://f.t0r.space/cover/24296026.webp)
