ace the coding interview with Python and JavaScript

Become proficient in deriving insights from time-series data and analyzing a model's performanceKey Features: Explore popular and modern machine learning methods including the latest online and deep learning algorithmsLearn to increase the accuracy of your predictions by matching the right model with the right problemMaster time-series via real-world case studies on operations management, digital marketing, finance, and healthcareBook Description: Machine learning has emerged as a powerful tool to understand hidden complexities in time-series datasets, which frequently need to be analyzed in areas as diverse as healthcare, economics, digital marketing, and social sciences. These datasets are essential for forecasting and predicting outcomes or for detecting anomalies to support informed decision making.This book covers Python basics for time-series and builds your understanding of traditional autoregressive models as well as modern non-parametric models. You will become confident with

Academic clinical posts offer doctors the highly rewarding opportunity to maintain both clinical and research careers, but these opportunities are fiercely competitive. This book provides medical students and doctors-in-training with a complete guide to preparing, applying and interviewing for such posts. Providing guidance on the typical UK academic pathways (including Academic Foundation Programme (AFP), Academic Clinical Fellowship (ACF), and Academic Clinical Lectureship (ACL)), candidates will learn how to choose a programme that suits their needs and experience. They will also get practical tips on how to best showcase their achievements and work portfolio in order to submit the highest quality application. A range of model answers to application and in-person questions are provided, together with a mock interview section demonstrating how to approach tricky questions and interviewers. Prepare for successful academic clinical interviews by following the tips and advice from autho

Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by Facebook's Artificial Intelligence Research Group.You'll start with a perspective on how and why deep learning with PyTorch has emerged as an path-breaking framework with a set of tools and techniques to solve real-world problems. Next, the book will ground you with the mathematical fundamentals of linear algebra, vector calculus, probability and optimization. Having established this foundation, you'll move on to key components and functionality of PyTorch including layers, loss functions and optimization algorithms. You'll also gain an understanding of Graphical Processing Unit (GPU) based computation, which is essential for training deep learning models

Specifically designed for linguists, this book provides an introduction to programming using Python for those with little to no experience of coding. Python is one of the most popular and widely-used programming languages as it's also available for free and runs on any operating system. All examples in the text involve language data and can be adapted or used directly for language research. The text focuses on key language-related issues: searching, text manipulation, text encoding and internet data, providing an excellent resource for language research. More experienced users of Python will also benefit from the advanced chapters on graphical user interfaces and functional programming.

Specifically designed for linguists, this book provides an introduction to programming using Python for those with little to no experience of coding. Python is one of the most popular and widely-used programming languages as it's also available for free and runs on any operating system. All examples in the text involve language data and can be adapted or used directly for language research. The text focuses on key language-related issues: searching, text manipulation, text encoding and internet data, providing an excellent resource for language research. More experienced users of Python will also benefit from the advanced chapters on graphical user interfaces and functional programming.

Discover the Most Comprehensible Beginner's Guide to Coding for Children, Packed with Fun Coding Activities and Games All Kids Will LoveDear friend, Do you have a little smartypants running around your home? Would you like to ensure the brightest possible future for your child? If so, then this book is a perfect choice for both of you.This bundle is an excellent choice for all children who are interested in the world of computers, programming, and coding. It is specially made for kids aged from 8 to 12 that have no prior knowledge of coding.Here is what this bundle can teach your child: Game-based learning - there's no better way for kids to learn than through playing and fun activities that will capture your child's attention.40+ fun coding activities and games - this bundle is packed with more than 40 fun activities that will introduce coding to your child and help them grasp the basic skills from a very young age.Easy-to-follow guidance - Straightforward directions and tips keep you

Deploy Python creatively and effectively through this collection of short coding projects carefullly curated by best-selling author and Python expert Al Sweigart. This curated collection of simple Pyt

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Designed as a textbook for a one or two-term introduction to mathematical statistics for students training to become data scientists, Foundations of Statistics for Data Scientists: With R and Python is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modelling. The book assumes knowledge of basic calculus, so the presentation can focus on 'why it works' as well as 'how to do it.' Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python.The book also introduces modern topics that do not normally appear in mathematical statistics texts but ar

The new edition of an introduction to the art of computational problem solving using Python.This book introduces students with little or no prior programming experience to the art of computational pro

Text is everywhere, and it is a fantastic resource for social scientists. However, because it is so abundant, and because language is so variable, it is often difficult to extract the information we want. There is a whole subfield of AI concerned with text analysis (natural language processing). Many of the basic analysis methods developed are now readily available as Python implementations. This Element will teach you when to use which method, the mathematical background of how it works, and the Python code to implement it.

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TheBig Fat Notebooks' big step up to high school continues! Announcing Biology,the third in the high schoolseries. With over 5 million copies in print since 2016, and sales escalating every year, theB

The Big Fat Notebooks go to high school! A lively, fully illustrated guide to acing high school geometry, with clear notes on the big ideas, helpful tips for memorizing processes and remembering defin

The Big Fat Notebooks go to high school! A lively, fully illustrated guide to acing high school chemistry, with clear notes on the big ideas, helpful tips for memorizing processes and remembering defi

Coding for kids without a computer--an offline skill-building book for ages 5 to 7 Coding helps kids develop analytical thinking, problem-solving abilities, and beyond In this exciting guide to coding for kids, your child will discover the core concepts of coding through colorful games and activities--without using a computer. These fun challenges can be done right inside the book or with everyday objects to help kids practice the same skills coders use, like writing clear instructions, recognizing patterns, and working efficiently. There's even a place for your beginner to invent their own codes This coding for kids book features: Coding fundamentals--Practice algorithms, loops, conditionals, optimization, debugging, and variables with games that help kids think like a computer programmer. Meet the coder crew--Explore coding for kids with a whole cast of characters, including Al the helper, Pixel the creative expert, Lo the problem-solver, Bug the pattern-spotter, and their robot dog