Data Science from Scratch with Python: Concepts and Practices with NumPy, Pandas, Matplotlib, Scikit-Learn and Keras - Tapa blanda

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9781733042635: Data Science from Scratch with Python: Concepts and Practices with NumPy, Pandas, Matplotlib, Scikit-Learn and Keras
Tapa blanda
ISBN 10: 1733042636 ISBN 13: 9781733042635
Editorial: AI Publishing LLC, 2019

Sinopsis

Data Science from scratch for Beginners with Hands-On Projects 

Are you looking for a hands-on approach to learn Data Science fast?

Do you need to start learning Machine Learning Fundamentals?

This book is for you.

This book is written for beginners and novices who want to develop fundamental data science skills and learn how to build models that learn useful information from data. This book will prepare the learner for a career or further learning that involves more advanced topics. It contains the introduction and very basic concepts used in data science. The learner is not required to have any prior knowledge but some basic knowledge of mathematics is required. This book is written for beginners and novices who want to develop fundamental data science skills and learn how to build models that learn useful information from data. This book will prepare the learner for a career or further learning that involves more advanced topics. It contains the introduction and very basic concepts used in data science. The learner is not required to have any prior knowledge but some basic knowledge of mathematics is required.

The working of each algorithm is traced back to its origin in probability, statistics or linear algebra which helps learners to understand the topics better. The concepts of probability and statistics are defined and explained at a rudimentary level to make things simple and easy to comprehend. For intuitive understanding, algorithms have been explained through proper visualizations and various examples.

While we will focus more on the techniques normally used in Data Science, we will also explain, in-details, all the Python libraries used in any data science project.

What this book offers... 

You will learn all about data Science starting from Python Coding, Data Manipulation and Preprocessing, Data Visualization then data modeling using Python. All the modules will contain hands-on projects using real-world datasets.

Clear and Easy to Understand Solutions

All solutions in this book are extensively tested by a group of beta readers. The solutions provided are simplified as much as possible so that they can serve as examples for you to refer to when you are learning a new skill.

What this book aims to do... 

This book is written with one goal in mind – to help beginners overcome their initial obstacles to learn Data Science from Scratch.

A lot of times, newbies tend to feel intimidated by Data Science Models and Coding.

The goal of this book is to isolate the different concepts so that beginners can gradually gain competency in the fundamentals and keys concepts before working on a project at the end of each chapter.

Beginners in Data Science does not have to be scary or frustrating when you take one step at a time.

Ready to start practicing and start learning Data Science from Scratch? Click the BUY button now to download this book

Topics Covered:

  • Preliminary to Understand Data Science
  • Overview of Python and Data Processing
  • Statistics and Probability
  • Supervised Learning Techniques
  • Unsupervised Learning Techniques
  • Neural Networks and Deep Learning
  • Reinforcement Learning Techniques
  • ..and more...

Click the BUY button and download the book now to start learning Data Science.

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

**GET YOUR COPY NOW, the price will be 24.99$ soon**

Learn and Build Data Science and Machine Learning Models from scratch!

Welcome to the Data Science from Scratch with Python Book!

The book offers you a solid introduction to the world of Data Science and Machine Learning. In this program, you’ll master fundamentals that will enable you to go further in the field, launch or advance a career, and join the next generation of Data Scientists talent that will help define a beneficial, new, AI-powered future for our world. You will study important topics such as Machine learning, Naïve Bayes, regressions, KNN, Decision trees and Random Forests, Ensemble modelling, K means Clustering, SVM, Neural Network and Deep learning.The book will give you the skills you need to understand the most recent important models in data science, and build and implement your own algorithms.The term is comprised of more than 15 chapters and practical project in each step. Building a project is one of the best ways to demonstrate the skills you've learned, and each project will contribute to an impressive professional portfolio that shows potential employers your mastery of data science techniques. Educational Objectives: Become an expert in data science, and learn to implement them from scratch and using frameworks like NumPy, Pandas, Scikit-learn and Keras. You will:
  • Learn to program in Python at a good level
  • Learn important concepts in Data Science
  • Learn how to deal with Real-world Data
  • Lean how to deal with Outlier and missing data
  • Build regression models
  • Build Classification models
  • Build Clustering models
Prerequisite Knowledge: The first chapters of the book will give you all the basic knowledge of probability, statistic, calculus (multivariable derivatives) and linear algebra (matrix multiplication needed for mastering data science. Please, take time to learn them.Contact Info: While going through the book, if you have questions about anything, you can reach us at contact@aispublishing.net.**GET YOUR COPY NOW, the price will be 24.99$ soon**

What’s Inside This Book?

  • Preliminary to understand Data Science
  • Different Data Science Elements
  • Important Concepts in Data Science and Machine Learning
  • Overview of Python and Data Processing
  • Python Data Science Tools
  • Dealing with Real-World Data
  • Statistics and Probability
  • Bayes Rule
  • Linear Regression
  • Logistic Regression
  • Support Vector Machines
  • Decision Trees and Random Forests
  • K-Nearest Neighbor
  • Naïve Bayes
  • Model Evaluation and Selection
  • K-Means Clustering
  • Hierarchical Clustering
  • Principal Component Analysis
  • Artificial Neural Networks
  • Convolution Neural Networks
  • Reinforcement Learning Techniques
  • Upper Confidence Bound
  • Thompson Sampling

EDITIORIAL REVIEWS

"I always find this data science introductory book very simple written and very easy to follow. I recommend it for any beginners want to learn Data Science from scratch.
The book is a very well practical guide step by step for data science with python. A Great resource for anyone who wants to get started on data science."
- Ph.D Amir Sharif, Data scientist Consultant at BCG. 

** MONEY BACK GUARANTEE BY AMAZON **

If you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform or contact us (our email inside the book).**GET YOUR COPY NOW, the price will be 24.99$ soon**

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
AI Publishing LLC
Año de publicación
2019
Idioma
Inglés
ISBN 10 
1733042636
ISBN 13 
9781733042635
Encuadernación
Tapa blanda
Número de páginas
260
Contacto del fabricante
no disponible
Persona responsable
no disponible