5 cheap books to master data science

Data science is a lucrative field with many future prospects. With the recent advancement of ai, it should come as no surprise that data science remains one of the most sought-after occupations. However, I know that it is not an easy field to break into.

There is a lot to learn if you want to enter the field of data science and understand many aspects of data. It also means that we need good material to learn because we don't want to waste time. This article will discuss five inexpensive books you can use to master data science.

What are these books? Let's get into it.

To master the field, we need to deeply understand the field we want to pursue. We need to understand data science to bring value to our work and avoid not getting the job at all.

He data science John D. Kelleher and Brendan Tierney's book could become your first step in understanding the data science industry in general. Priced at $9, you would learn the following from the book:

1. History of data science
2. Data science applications
3. The tools of data science
4. Ethical concerns in the application of data science
5. Career growth in data science

This book is a great introductory book for anyone looking to enter the field of data science or better understand the concept of data science.

Programming skills have already become the backbone of data scientists and every company lists them as requirements. The requirement is usually the Python language, the programming language of modern data scientists. Without knowledge of Python, there is a high chance that we will not be able to do our job properly.

Python data analysis The book by Avinash Navlani, Armando Fandango and Ivan Idris (author) would provide a complete learning on how to navigate the field of data science with the necessary skills in Python. What you would learn includes:

1. Python Core Libraries and Data Handling
2. Statistical and mathematical foundations.
3. Advanced data analysis techniques
4. Specialized data analysis
5. Computational efficiency with Dask

The price of the book is around $16, which is in the cheaper range compared to other books out there. Although the value of this book is great.

While data scientists need to know the programming language, we also need to understand statistical theory. Our data analysis and machine learning algorithms were based on a statistical methodology and we needed to understand basic statistics to understand the data activity we were performing.

Naked statistics: taking the fear out of data, written by Charles Wheelan, breaks down statistical concepts in a fun way and with application examples. The book includes cases for:

1. Applications of standard error and CI in cases of political surveys.
2. Regression analysis on risk of health problems in the United Kingdom.
3. Netflix and Target statistical inference applications for product recommendations.

There are still many statistical concepts that you will learn from this book. With the price of $8, you can easily understand why statistics are important in data science.

After having a basic understanding of data science, we should learn about machine learning algorithm. The primary tool of data scientists is the ML model, and it is essential to understand how each model works and why we use them.

The Hitchhiker's Guide to Machine Learning Algorithms by Devin Schumacher, Francis La Bounty Jr. and Devanshu Mahapatra would serve as a reference to better understand the machine learning algorithm. He will learn the following concepts from this book:

1. Classification and regression techniques
2. Clustering algorithms
3. Neural networks and deep learning
4. Optimization and problem solving algorithms
5. Ensemble methods and dimensionality reduction techniques.
6. Reinforcement learning

Each chapter is an independent section, so we can jump to any chapter that interests us. For $12, you would get a wealth of knowledge, from theoretical applications to real-world applications of machine learning.

Data science is not just about programming, machine learning, or statistics. It's about generating value from the data we have. So, it is crucial for any data scientist to understand how to communicate our technical results in a way that stakeholders or non-technical people understand.

In it Data information delivered In Mo Villagran's book, he explains that data professionals struggle to deliver value due to poor communication with stakeholders, unrealistic expectations fueled by marketing hype, and the underutilization of most data products. With her experience, she composes seven steps we can follow to have better communication and assess the needs of stakeholders.

For $15, you can learn all of these steps quickly and get better at the interpersonal skills that are always required.

Data science is a difficult field to break into. That's why these five budget-friendly books will help you master data science. The books include:

1. Data Science (MIT Press Essential Knowledge Series)
2. Python data analysis
3. Naked statistics: taking the fear out of data
4. The Hitchhiker's Guide to Machine Learning Algorithms
5. Data information delivered

Cornellius Yudha Wijaya He is an assistant data science manager and data writer. While working full-time at Allianz Indonesia, she loves sharing Python tips and data through social media and print media.