“…What you will learn Understand the basics of relational databases, relational algebra, and data modeling Install a PostgreSQL server, create a database, and implement your data model Create tables and views, define indexes and stored procedures, and implement triggers Make use of advanced data types such as Arrays, hstore, and JSONB Connect your Python applications to PostgreSQL and work with data efficiently Identify bottlenecks to enhance reliability and performance of database applications Who this book is for This book is for you if you're interested in learning about PostgreSQL from scratch. …”

“…You'll then understand how to express choices or alternatives directly in the type system using variants, polymorphic variants, and generalized algebraic data types. You'll also get to grips with sum types, build sophisticated data types from generics, and explore functions that express change in the types of values. …”

“…It is designed to benefit a wide range of people, including long/short market participants, quantitative participants, proprietary traders, commodity trading advisors, retail investors (pro retailers, students, and retail quants), and long-only investors.At least 2 years of active trading experience, intermediate-level experience of the Python programming language, and basic mathematical literacy (basic statistics and algebra) are expected…”

“…To fellow statisticians, the author demonstrates how to present statistical output to non-statisticians to ensure that the statistical results are correctly understood and properly applied to real-world tasks and decisions. The book avoids algebra and proofs, but it does supply code written in R for those readers who are motivated to work out examples. …”

“…What You Will Learn Acquire the practical knowledge to use the main functional design patterns Realign some imperative and object-oriented principles under the functional approach Develop your confidence in building and combining first-order and higher-order functions Learn to use core language pattern matching effectively Make use of native F# algebraic data types in place of custom-built classes Recognize and measure the difference in resource consumption between sequences and materialized data collections Navigate and use F# Core libraries with ease by seeing patterns behind specific library functions Master writing generic polymorphic code In Detail Following design patterns is a well-known approach to writing better programs that captures and reuses high-level abstractions that are common in many applications. …”

“…Skill Level Intermediate Learn How To Represent text Model topics Conduct sentiment analysis Understand word2vec word embeddings Define GloVe Apply language detection Who Should Take This Course Data scientists with an interest in natural language processing Course Requirements Basic algebra Calculus and statistics Programming experience Lesson Descriptions Lesson 1: Text Representations The first step in any NLP application is to establish the representations of text and numbers. …”

“…What You Will Learn Understand what functional programming is and why it matters Understand custom operators, function composition, currying, recursion, and memoization Explore algebraic data types, pattern matching, generics, associated type protocols, and type erasure Get acquainted with higher-kinded types and higher-order functions using practical examples Get familiar with functional and non-functional ways to deal with optionals Make use of functional data structures such as semigroup, monoid, binary search tree, linked list, stack, and lazy list Understand the importance of immutability, copy constructors, and lenses Develop a backend API with Vapor Create an iOS app by combining FP, OOP, FRP, and POP paradigms In Detail Swift is a multi-paradigm programming language enabling you to tackle different problems in various ways. …”

“…Whether you're a student, professional, or manager, this video course will prepare you for the quantum computing revolution--and expand your career options, too. Master the linear algebra and other mathematical skills you'll need Explore key physics ideas, such as quantum states and uncertainty Review data structures, algorithms, and computing complexity Work with probability and set theory in quantum computing Familiarize yourself with basic quantum theory and formulae Understand quantum entanglement and quantum key distribution Discover how quantum computers are architected and built Explore several leading quantum algorithms Compare quantum and conventional asymmetric algorithms See how quantum computing might break traditional cryptography Discover several approaches to quantum-resistant cryptography Start coding with Q#, Microsoft's quantum programming language Simulate quantum gates and algorithms with QASM If you prefer a multimodal approach to learning, check out the Quantum Computing Fundamentals book by Chuck Easttom!…”

“…Here you will learn about algebraic types such as std::optional, vocabulary types such as std::function, smart pointers, and synchronization primitives such as std::atomic and std::mutex. …”

“…What you will learn Become familiar with the basic features of the TensorFlow library Get to know Linear Regression techniques with TensorFlow Learn SVMs with hands-on recipes Implement neural networks to improve predictive modeling Apply NLP and sentiment analysis to your data Master CNN and RNN through practical recipes Implement the gradient boosted random forest to predict housing prices Take TensorFlow into production Who this book is for If you are a data scientist or a machine learning engineer with some knowledge of linear algebra, statistics, and machine learning, this book is for you. …”

“…By the end of the book, you will have implemented all primitive and some advanced collision tests, and you will be able to read on geometry and linear Algebra formulas to take forward to your own games! …”

“…What You Will Learn Use new features to write structured and readable object-oriented code Find out how to use lambdas and higher order functions to write clean, reusable, and simple code Write unit tests and integrate Kotlin tests with Java code in a transitioning code base Write real-world production code in Kotlin in the style of microservices Leverage Kotlin's extensions to the Java collections library Use destructuring expressions and find out how to write your own Write code that avoids null pointer errors and see how Java-nullable code can integrate with features in a Kotlin codebase Discover how to write functions in Kotlin, see the new features available, and extend existing libraries Learn to write an algebraic data types and figure out when they should be used In Detail Kotlin has been making waves ever since it was open sourced by JetBrains in 2011; it has been praised by developers across the world and is already being adopted by companies. …”

“…Strong working knowledge of Python, linear algebra, and machine learning is a must. Downloading the example code for this ebook: You can download the example code files for this ebook on GitHub at the following link: https://github.com/TrainingByPackt/Deep-Learning-for-Natural-Language-Processing . …”

“…No previous mathematical understanding is required beyond basic algebra, probability, and statistics: wherever more advanced math is required, the authors explain it fully. …”

“…You'll need basic knowledge of the Python programming language, AWS, linear algebra, probability, and networking concepts before you get started with this handbook…”

“…Before you get started with this book, you'll need a good understanding of calculus, as well as linear algebra…”

“…What you will learnGrasp important pre-steps in building NLP applications like POS taggingUse transfer and weakly supervised learning using libraries like SnorkelDo sentiment analysis using BERTApply encoder-decoder NN architectures and beam search for summarizing textsUse Transformer models with attention to bring images and text togetherBuild apps that generate captions and answer questions about images using custom TransformersUse advanced TensorFlow techniques like learning rate annealing, custom layers, and custom loss functions to build the latest DeepNLP modelsWho this book is forThis is not an introductory book and assumes the reader is familiar with basics of NLP and has fundamental Python skills, as well as basic knowledge of machine learning and undergraduate-level calculus and linear algebra. The readers who can benefit the most from this book include intermediate ML developers who are familiar with the basics of supervised learning and deep learning techniques and professionals who already use TensorFlow/Python for purposes such as data science, ML, research, analysis, etc…”

“…Learners should have a basic knowledge of linear algebra, calculus, and Python programming to effectively understand matrix calculus. …”

“…A basic knowledge of Python, AWS, linear algebra, probability, and cloud infrastructure is required before you get started with this handbook…”

“…This book skips the confused academic jargon and offers clear explanations that require only basic algebra. As you go, you'll build interesting projects with Python, including models for spam detection and image recognition. …”