Ethan Williams has 3 audiobooks on Listento.it, narrated by 2 narrators. The most-rated is Deep Learning with Python.
Python for Data Science
Summary
Python for Data Science is a comprehensive guide about how to perform data science with Python. This book is for students, researchers, and developers who are technically minded and have a wide background in writing code as well as using numerical and computational tools. However, many of you may not wish to learn Python, but instead wish to learn the language in hopes of utilizing it as a means for computational and data-intensive science. The aim of this book is not meant to serve as a kind of introduction to Python or even programming in general; we presume listeners will get their hands on this, already possess ample amount of knowledge in the Python language, which includes assigning variables, defining functions, controlling a program's flow, calling methods of objects, and other basic operations. Rather, the book was put together to assist users of Python to understand how to use the data science stack of Python – with libraries including NumPy, Pandas, Matplotlib and other such tools - with the aim of effectively manipulating, storing, and getting data insight. In this book, we'll cover a variety of topics, including several libraries, such as NumPy that offers the ndarray for efficient manipulation and storage of dense data arrays in Python. Then you'll be able to learn how to manipulate data using Pandas, a library that offers the DataFrame object for efficient manipulation and storage of columnar/label data in Python. After that, we'll talk about the Matplotlib library and how it provides a range of flexible data visualization capabilities in Python. Then we'll talk the types of machine learning involved including supervised and unsupervised learning. Lastly, we'll finish with multiple regression analysis, which is a combination of techniques that help us study the straight-line relations between two or more variables. In addition, this book is backed by a series of examples and case studies to help clarify anything that is a little too hard for you to absorb. We are confident that you will make fine a data scientists going forward!
©2020 Ethan Williams (P)2020 Ethan Williams
Python Data Analytics
Summary
Have you ever thought about data analytics? Are you looking for an excellent tool to use in your data analysis? Well, you have come to the right place. Python is one of the best tools that you can use for your data analysis for several reasons. Apart from the flexibility and ease of learning it offers, if you are trying something creative that no one has ever done before, then Python is the best way to go. It is also ideal for any developer who is looking for a program that will allow them to script websites and applications. The best thing that I love about Python is its readability and simplicity, which goes a long way in boosting a gradual and relatively low learning curve. This is precisely what makes Python an ideal tool for beginners. Python is an open-source program that also has built a valuable community-based model. It is designed to run on different operating systems ranging from Windows to Linux environments. The good thing with this language is that you can easily port it to a wide range of platforms. There are so many open-source python libraries such as data manipulation, statistics, visualization, machine learning, mathematics, and natural language processing, among others. Did you know that anything that could go wrong goes wrong? Think about it. If you are using something that you did not have to pay for, will you get the help that you need quickly? Well, you'll expect the answer to be a definite "no"! The most fortunate thing with Python is that it is widely used both in academics and industrial levels. This means that there are so many analytical libraries at your disposal. Therefore, if as a python user, you get stuck and need help, you can get it quickly on Stack Overflow’s user-contributed codes, mailing lists, and documentation. The more python gains popularity, the more the users keep contributing information on their experience with the programming language. That said, one thing that is important to note is that Python is not an overly complicated language to use. The price is right, and you have all the support you need out there to ensure that while working on your project, you do not come to a screeching halt whenever you hit a snag.
©2019 Ethan Williams (P)2019 Ethan Williams
Deep Learning with Python
Summary
You have made a perfect choice to consider learning Python and, most importantly, to develop your skills in the programming world. A good choice comes with good tidings - you are looking at a highly comprehensive beginners’ guidebook that will provide you with all the necessary steps and tips to get started. Deep Learning with Python is packed with basic beginners’ concepts, detailed examples, and extra-reminder exercises. Newbies are totally welcome to dive in! You do not need any experience with programming, whatsoever. Just have a notepad ready because taking short notes helps and get ready to play around with the samples and do a whole lot of coding! The program was developed in December 1989 by Guido van Rossum. Guido’s passion and hobby was to write and learn new codes that were available during his time. It is documented that he developed the Python programming language while interacting and learning the ABC programming language. This is one of the best languages that you can choose to begin learning and at the end have a successful career in it. I know that you are going to have a very nice experience in this programming language. In summary, since the programming language was open-sourced, we expect a lot of advancements and developments on the language that will make it simpler and easier to use over the coming years.
©2019 Ethan Williams (P)2019 Ethan Williams