The Ultimate Guide to Snowpark. Design and deploy Snowflake Snowpark with Python for efficient data workloads

Shankar Narayanan SGS, Vivekanandan SS, Jeff Hollan

Snowpark is a powerful framework that helps you unlock numerous possibilities within the Snowflake Data Cloud. However, without proper guidance, leveraging the full potential of Snowpark with Python can be challenging. Packed with practical examples and code snippets, this book will be your go-to guide to using Snowpark with Python successfully.The Ultimate Guide to Snowpark helps you develop an understanding of Snowflake Snowpark and how it enables you to implement workloads in data engineering, data science, and data applications within the Data Cloud. From configuration and coding styles to workloads such as data manipulation, collection, preparation, transformation, aggregation, and analysis, this guide will equip you with the right knowledge to make the most of this framework. You'll discover how to build, test, and deploy data pipelines and data science models. As you progress, you’ll deploy data applications natively in Snowflake and operate large language models (LLMs) using Snowpark container services.By the end of this book, you'll be able to leverage Snowpark's capabilities and propel your career as a Snowflake developer to new heights.

Hands-On Deep Learning Algorithms with Python. Master deep learning algorithms with extensive math by implementing them using TensorFlow

Sudharsan Ravichandiran

Deep learning is one of the most popular domains in the AI space that allows you to develop multi-layered models of varying complexities. This book introduces you to popular deep learning algorithms—from basic to advanced—and shows you how to implement them from scratch using TensorFlow. Throughout the book, you will gain insights into each algorithm, the mathematical principles involved, and how to implement it in the best possible manner. The book starts by explaining how you can build your own neural networks, followed by introducing you to TensorFlow, the powerful Python-based library for machine learning and deep learning. Moving on, you will get up to speed with gradient descent variants, such as NAG, AMSGrad, AdaDelta, Adam, and Nadam. The book will then provide you with insights into recurrent neural networks (RNNs) and LSTM and how to generate song lyrics with RNN. Next, you will master the math necessary to work with convolutional and capsule networks, widely used for image recognition tasks. You will also learn how machines understand the semantics of words and documents using CBOW, skip-gram, and PV-DM. Finally, you will explore GANs, including InfoGAN and LSGAN, and autoencoders, such as contractive autoencoders and VAE. By the end of this book, you will be equipped with all the skills you need to implement deep learning in your own projects.

Learning Cocos2d-x Game Development. Learn cross-platform game development with Cocos2d-x

Siddharth Shekar

Big Data Analytics. Real time analytics using Apache Spark and Hadoop

Venkat Ankam

Big Data Analytics book aims at providing the fundamentals of Apache Spark and Hadoop. All Spark components – Spark Core, Spark SQL, DataFrames, Data sets, Conventional Streaming, Structured Streaming, MLlib, Graphx and Hadoop core components – HDFS, MapReduce and Yarn are explored in greater depth with implementation examples on Spark + Hadoop clusters. It is moving away from MapReduce to Spark. So, advantages of Spark over MapReduce are explained at great depth to reap benefits of in-memory speeds. DataFrames API, Data Sources API and new Data set API are explained for building Big Data analytical applications. Real-time data analytics using Spark Streaming with Apache Kafka and HBase is covered to help building streaming applications. New Structured streaming concept is explained with an IOT (Internet of Things) use case. Machine learning techniques are covered using MLLib, ML Pipelines and SparkR and Graph Analytics are covered with GraphX and GraphFrames components of Spark. Readers will also get an opportunity to get started with web based notebooks such as Jupyter, Apache Zeppelin and data flow tool Apache NiFi to analyze and visualize data.

Hands-On Generative Adversarial Networks with PyTorch 1.x. Implement next-generation neural networks to build powerful GAN models using Python

John Hany, Greg Walters

With continuously evolving research and development, Generative Adversarial Networks (GANs) are the next big thing in the field of deep learning. This book highlights the key improvements in GANs over generative models and guides in making the best out of GANs with the help of hands-on examples.This book starts by taking you through the core concepts necessary to understand how each component of a GAN model works. You'll build your first GAN model to understand how generator and discriminator networks function. As you advance, you'll delve into a range of examples and datasets to build a variety of GAN networks using PyTorch functionalities and services, and become well-versed with architectures, training strategies, and evaluation methods for image generation, translation, and restoration. You'll even learn how to apply GAN models to solve problems in areas such as computer vision, multimedia, 3D models, and natural language processing (NLP). The book covers how to overcome the challenges faced while building generative models from scratch. Finally, you'll also discover how to train your GAN models to generate adversarial examples to attack other CNN and GAN models.By the end of this book, you will have learned how to build, train, and optimize next-generation GAN models and use them to solve a variety of real-world problems.

Solutions Architect's Handbook. Kick-start your solutions architect career by learning architecture design principles and strategies

Saurabh Shrivastava, Neelanjali Srivastav, Kamal Arora

Becoming a solutions architect gives you the flexibility to work with cutting-edge technologies and define product strategies. This handbook takes you through the essential concepts, design principles and patterns, architectural considerations, and all the latest technology that you need to know to become a successful solutions architect.This book starts with a quick introduction to the fundamentals of solution architecture design principles and attributes that will assist you in understanding how solution architecture benefits software projects across enterprises. You'll learn what a cloud migration and application modernization framework looks like, and will use microservices, event-driven, cache-based, and serverless patterns to design robust architectures. You'll then explore the main pillars of architecture design, including performance, scalability, cost optimization, security, operational excellence, and DevOps. Additionally, you'll also learn advanced concepts relating to big data, machine learning, and the Internet of Things (IoT). Finally, you'll get to grips with the documentation of architecture design and the soft skills that are necessary to become a better solutions architect.By the end of this book, you'll have learned techniques to create an efficient architecture design that meets your business requirements.

Test-Driven Development with Java. Create higher-quality software by writing tests first with SOLID and hexagonal architecture

Alan Mellor

Test-driven development enables developers to craft well-designed code and prevent defects. It’s a simple yet powerful tool that helps you focus on your code design, while automatically checking that your code works correctly. Mastering TDD will enable you to effectively utilize design patterns and become a proficient software architect.The book begins by explaining the basics of good code and bad code, bursting common myths, and why Test-driven development is crucial. You’ll then gradually move toward building a sample application using TDD, where you’ll apply the two key rhythms -- red, green, refactor and arrange, act, assert. Next, you’ll learn how to bring external systems such as databases under control by using dependency inversion and test doubles. As you advance, you’ll delve into advanced design techniques such as SOLID patterns, refactoring, and hexagonal architecture. You’ll also balance your use of fast, repeatable unit tests against integration tests using the test pyramid as a guide. The concluding chapters will show you how to implement TDD in real-world use cases and scenarios and develop a modern REST microservice backed by a Postgres database in Java 17.By the end of this book, you’ll be thinking differently about how you design code for simplicity and how correctness can be baked in as you go.

Learn Robotics Programming. Build and control AI-enabled autonomous robots using the Raspberry Pi and Python - Second Edition

Danny Staple

We live in an age where the most complex or repetitive tasks are automated. Smart robots have the potential to revolutionize how we perform all kinds of tasks with high accuracy and efficiency. With this second edition of Learn Robotics Programming, you'll see how a combination of the Raspberry Pi and Python can be a great starting point for robot programming.The book starts by introducing you to the basic structure of a robot and shows you how to design, build, and program it. As you make your way through the book, you'll add different outputs and sensors, learn robot building skills, and write code to add autonomous behavior using sensors and a camera. You'll also be able to upgrade your robot with Wi-Fi connectivity to control it using a smartphone. Finally, you'll understand how you can apply the skills that you've learned to visualize, lay out, build, and code your future robot building projects.By the end of this book, you'll have built an interesting robot that can perform basic artificial intelligence operations and be well versed in programming robots and creating complex robotics projects using what you've learned.