Ultimate Step by Step Guide to Deep Learning Using Python

Neural Networks concepts explained in simple terms for beginners

Non-Fiction - Business/Finance
212 Pages
Reviewed on 07/19/2020
Buy on Amazon

This author participates in the Readers' Favorite Book Review Exchange Program, which is open to all authors and is completely free. Simply put, you agree to provide an honest review an author's book in exchange for the author doing the same for you. What sites your reviews are posted on (B&N, Amazon, etc.) and whether you send digital (eBook, PDF, Word, etc.) or hard copies of your books to each other for review is up to you. To begin, click the purple email icon to send this author a private email, and be sure to describe your book or include a link to your Readers' Favorite review page or Amazon page.

This author participates in the Readers' Favorite Book Donation Program, which was created to help nonprofit and charitable organizations (schools, libraries, convalescent homes, soldier donation programs, etc.) by providing them with free books and to help authors garner more exposure for their work. This author is willing to donate free copies of their book in exchange for reviews (if circumstances allow) and the knowledge that their book is being read and enjoyed. To begin, click the purple email icon to send this author a private email. Be sure to tell the author who you are, what organization you are with, how many books you need, how they will be used, and the number of reviews, if any, you would be able to provide.

    Book Review

Reviewed by Tammy Ruggles for Readers' Favorite

Ultimate Step by Step Guide to Deep Learning Using Python by Daneyal Anis is the perfect book for those looking to take the leap into a career of artificial intelligence, data mining, and deep machine learning. With so many careers impacted by Covid-19, switching careers into something more stable can be a good choice. This book lays out the field of data mining in easy-to-understand terms. Even if you are unfamiliar with artificial intelligence, Anis helps you get a solid understanding of the concepts. This is a good introduction for those who may be curious about the field, have an interest but don't know where to start, or are ready to jump in with both feet. When you start reading the book, the text may seem like a foreign language, but as you keep reading, the terms, concepts, and techniques become clearer. You will learn about regularization value, hyperparameters, data cleaning, and much more. From the beginning, Anis defines each idea, like artificial intelligence, which is basically a computer/machine that learns to think and interpret based on the information it is fed by humans. The author likens it to a child learning as he/she grows older. Did you know there is good data and bad data? What exactly is a neural network layer? How do algorithms work? And how does a computer read or understand the concept of colors? Anis explains it all.

If you've ever learned a new skill, from fishing, working on computers, or using a sewing machine, then you know that at first, the task can be daunting, but if you have a good teacher, everything makes sense. This book is that teacher. Python is a programming language that you can learn and the bonus material found in the book, like how to use Cloud Technologies, is even more impressive. If you're looking for a new career in computer technology, data mining, or modeling, and are looking to become financially successful, Data Science is the next big area to get into. The title alone can sound intimidating, but this author has a way of simplifying it so that you can grasp whether you want to pursue this as your next-level career choice. His use of images, graphs, charts, and examples is impressive, which helps the reader understand the material. The glossary at the end is extremely useful as well. It may help to read it first, and then again at the end. Ultimate Step by Step Guide to Deep Learning Using Python by Daneyal Anis is the premier primer for those brave enough to make a big career change.

Mamta Madhavan

Ultimate Step by Step Guide to Deep Learning Using Python by Daneyal Anis is a handy manual that explains in simple terms the concepts of artificial intelligence, deep learning, and machine learning to beginners. Artificial intelligence and machine learning are two important skills in great demand now in the job market. This book is the perfect choice to understand the concepts of neural networks and how to differentiate between machine learning models and deep learning models. For readers looking to code in Python, build new machine learning and deep learning models from scratch, speak confidently about statistical analysis techniques, and learn how to clean and prepare data for analytics, this book is the perfect tool to help.

Daneyal Anis makes the topic easy to comprehend and for readers to grasp the concept. The handling of the subject is structured, methodical, and interesting and that makes it easy for readers to take a step towards becoming experts in the world of Artificial intelligence, machine learning, and Python. For readers who have been overwhelmed by these topics and found it difficult to understand, this book is a helpful guide that not only speaks about the key concepts but also elaborates on machine learning algorithms like Linear Regression, Logistical Regression, Decision Trees, Support Vector Machines (SVMs), and others useful in mastering machine learning and data science. There is a lot of information in the book and the author makes it easy for readers to understand using charts and diagrams. The glossary of terms, definitions, and references help readers learn more about the topic.

K.C. Finn

Ultimate Step by Step Guide to Deep Learning Using Python: Neural Networks concepts explained in simple terms for beginners is a work of non-fiction in the business, technology, and guidebook sub-genres, and was penned by author Daneyal Anis. This concise but highly informative guide offers, as the title suggests, to take readers from little or no knowledge of Python coding through its full utilization into the world of dark analytics. Featuring many different aspects of artificial intelligence and how coding and analysis works, the book shows readers how to move into the career path of becoming a data scientist, a fast-growing and desirable profession for the modern world.

Author Daneyal Anis really has thought of everything that a budding data scientist would want to know in this excellent book. I would certainly recommend it as a first guide for anyone thinking about coding and data analysis as a career move because it offers a comprehensive organization of all the necessary topics and shows you where to expand after this grounding. I enjoyed the narrative style very much; formal and professional but not packed with jargon, so it was really easy to understand. The ideas, too, are phrased in an accessible fashion and explained in clear terms, and the step by step code examples are an absolute must. Overall, Ultimate Step by Step Guide to Deep Learning Using Python delivers exactly what it promises, and is sure to fast become the essential starting point for readers looking to learn about data analysis.

Rabia Tanveer

Ultimate Step by Step Guide to Deep Learning Using Python: Neural Networks Concepts Explained In Simple Terms For Beginners by Daneyal Anis is a simple, easy, and complete guide on Python. It is perfect for aspiring data scientists, developers, or anyone who wishes to learn about this programming language. Most aspiring programmers are a little intimidated by Python, but if they have the right guidance, they can master it in no time. This book simply states the purpose of the programming language, gives the right information in the simplest of manners, and then gives the reader enough material to master the language. The reader will understand Deep Learning, Machine Learning, and Artificial Intelligence. Once they know about that, the author then takes the reader one step further and makes concepts of algorithms, networks, and libraries easier to understand. Other than that, the reader will learn to make models from scratch, analyze data, and become confident in their coding abilities.

I have read the previous guide by Daneyal Anis on Predictive modeling concepts and found his style of writing to be very helpful. I personally have an interest in learning Python and I find his method of guidance to be helpful and refreshing. He not only gives the right information; he also makes it easy to digest and implement. For a newbie, such information is very important. Python can be complex if it is not taught properly, but this guide is a great way to understand the basics and implement them as well. He never hurries readers but encourages them to take their time and set their own pace. I am sure the tips at the end of the book will be very helpful for any professional data scientist or developer expecting to move forward in their career and hoping to succeed. I found this book to be very educational and informative for beginners.

Christian Sia

Ultimate Step by Step Guide to Deep Learning Using Python: Neural Networks Concepts Explained in Simple Terms for Beginners by Daneyal Anis is a simplified, easy-to-read book on Python and machine learning. Designed for beginners, this book offers a clear introduction to artificial learning, machine learning, and deep learning. It is a book for readers who are interested in training a machine so that it can perceive and interact with the data it is receiving from its physical environment, understand and learn from the data, and provide intelligent responses. This book provides the tools readers need to train machines to predict the future. The author defines the concepts and machine learning algorithms developed in this book such as linear regression, logistical regression, decision trees, support vector machines, and more. Readers will not only understand what is involved in deep learning but will follow a practical step-by-step guide to mastering it.

Daneyal Anis’s book stands out in that it offers learning in a way that readers not familiar with Python coding will find it accessible. The step-by-step guide is reinforced by the use of examples and clear explanations to make learning easier for readers. The book is filled with visual aids that explain complex concepts, and the author gives flesh to deep learning and machine learning by relating the concepts to real-world examples and images. This book provides the tools that readers who want to excel in data science and machine learning need, a real gem, especially for beginners. The book is well-written and I particularly enjoyed the simplicity with which the author defines key concepts discussed in the book, the step-by-step guide, moving from simpler to more complex ideas. Ultimate Step by Step Guide to Deep Learning Using Python is the place to start. As someone with no background in Python, I found this book to be written in language that is very accessible and with clarity.