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Price: 6.00 USD | Size: 5.9 GB | Duration :3.33  Hours | 37 Video seasons |  ★★★★★   4.5 BRAND : Expert TRAINING | ENGLISH | INSTANT DOWNLOAD | Bonus PDF Guides Data Cleansing Master Class in Python Online Course & PDF guides About this video Data preparation may be the most important part of a machine learning project. It is the most time-consuming part, although it is the least discussed topic. Data preparation, sometimes referred to as data preprocessing, is the act of transforming raw data into a form that is appropriate for modeling. Machine learning algorithms require input data to be numbered, and most algorithm implementations maintain this expectation. Therefore, if your data contains data types and values that are not numbers, such as labels, you will need to change the data into numbers. Further, specific machine learning algorithms have expectations regarding the data types, scale, probability distribution, and relationships between input variables, and you may need to

Price: 6.00 USD | Size: 3.4 GB | Duration : 11  Hours | 100+ Video Lessons |  ★★★★★  4.2 BRAND : Expert TRAINING | ENGLISH | INSTANT DOWNLOAD Data Analyst  Business Intelligence Python Pandas SQL Online Course What you'll learn Data Querying Data manipulation Data Visualisation Data Cleansing Data Transformation Description The data analyst serves as a gatekeeper for an organization's data so stakeholders can understand data and use it to make strategic business decisions. Business intelligence (BI) helps organizations analyze historical and current data, so they can quickly uncover actionable insights for making strategic decisions. Business intelligence tools make this possible by processing large data sets across multiple sources and presenting findings in visual formats that are easy to understand and share. There are four keys steps that business intelligence follows to transform raw data into easy-to-digest insights for everyone in the organization to use. The first three

Data Science Fundamentals for Python and MongoDB PDF Guide  Related to: python for data science data science course how to become data scientist data science meaning python mongodb tutorial python and mongodb projects python mongodb connection w3schools w3schools mongodb python python mongodb orm python mongodb connection example mongodb w3schools  

Price: Free Download | ISBN: 978-3-319-X8316-6 |20 July 2016 | 295 Pages|  ★★★★★4.2 BRAND : Expert TRAINING | ENGLISH | INSTANT DOWNLOAD An Introduction to Statistics with Python  With Applications in the Life Sciences PDF Guide   This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. Working code and data for Python solutions for each test, together with easy-to-follow Python examples, can be reproduced by the reader and reinforce their immediate understanding of the topic. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis and an interesting alternative to R. The book is intended for master and PhD students, mainly from the life and med

Price: Free Download | ISBN:  978148426X003 |  December 22, 2020  | 4852 Pages| ★★★★★4.7  BRAND : Expert TRAINING | ENGLISH | INSTANT DOWNLOAD  A Python Data Analyst’s Toolkit Learn Python And Python-based Libraries With Applications In Data Analysis And Statistics Explore the fundamentals of data analysis, and statistics with case studies using Python. This book will show you how to confidently write code in Python, and use various Python libraries and functions for analyzing any dataset. The code is presented in Jupyter notebooks that can further be adapted and extended. This book is divided into three parts - programming with Python, data analysis and visualization, and statistics. You'll start with an introduction to Python - the syntax, functions, conditional statements, data types, and different types of containers. You'll then review more advanced concepts like regular expressions, handling of files, and solving mathematical problems with Python. The second part of the b

Price: Free Download |      ISBN 366249XX63     |MARCH 2015 | 302 Pages|  ★★★★★4.7  BRAND : Expert TRAINING | ENGLISH | INSTANT DOWNLOAD A Primer on Scientific Programming with Python PDF Guide The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathe

Price: 10.00 USD | Size: 9.2 GB | Duration : 5 +  Hours | 63 Video Lessons |  ★★★★★  4.6 BRAND : Expert TRAINING | ENGLISH | INSTANT DOWNLOAD Basic Statistics & Regression for Machine Learning in Python Online Course & PDF Guides  A quick and easy guide on statistical regression for machine learning    What you'll learn Python Basics, Statistics and Regression behind Machine Learning in Python and also using Manual Calculations Course Contents PART-01 01.01-course introduction and table of contents 02.01-environment setup-part 1 02.02-environment setup-part 2 03.01-essential components included in anaconda 04.01-python basics-assignment 05.01-python basics-flow control-part 1 05.02-python basics-flow control-part 2 06.01-python basics-list and tuples 07.01-python basics-dictionary and functions-part 1 07.02-python basics-dictionary and functions-part 2 08.01-numpy basics-part 1 08.02-numpy basics-part 2 09.01-matplotlib basics-part 1 09.02-matplotlib basics-part 2 10.01-bas