From fundamental techniques to advanced strategies for handling big data, visualization, and more, this book equips you with skills to excel in real-world data analysis projects. Free with your book: DRM-free PDF version + access to Packt's next-gen Reader\*Key FeaturesThis book targets features in pandas 2.x and beyondPractical, easy to implement recipes for quick solutions to common problems in data using pandasMaster the fundamentals of pand...

Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process.Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduct...

Unleash the power of computer vision with Python using OpenCV Key FeaturesBook DescriptionOpenCV 3 is a state-of-the-art computer vision library that allows a great variety of image and video processing operations. Some of the more spectacular and futuristic features such as face recognition or object tracking are easily achievable with OpenCV 3. Learning the basic concepts behind computer vision algorithms, models, and OpenCV's API will enable the dev...

Powerful, flexible, and easy to use, Python is an ideal language for building software tools and applications for life science research and development. This unique book shows you how to program with Python, using code examples taken directly from bioinformatics. In a short time, you'll be using sophisticated techniques and Python modules that are particularly effective for bioinformatics programming.Bioinformatics Programming Using Python is perfect for anyone involved wi...

Learn the data skills necessary for turning large sequencing datasets into reproducible and robust biological findings. With this practical guide, youâ??ll learn how to use freely available open source tools to extract meaning from large complex biological data sets.At no other point in human history has our ability to understand lifeâ??s complexities been so dependent on our skills to work with and analyze data. This intermediate-level book teaches the general computational and da...

Build smart, efficient, and fast enterprise-grade web implementation of the microservices architecture that can be easily scaled.Key FeaturesWrite easy-to-maintain lean and clean code with Kotlin for developing better microservicesScale your Microserivces in your own cloud with Docker and Docker SwarmExplore Spring 5 functional reactive web programming with Spring WebFluxBook DescriptionWith Google's inclusion of first-class ...

Fully build and productionize end-to-end machine learning solutions using Azure Machine Learning ServiceKey FeaturesAutomate complete machine learning solutions using Microsoft AzureUnderstand how to productionize machine learning modelsGet to grips with monitoring, MLOps, deep learning, distributed training, and reinforcement learningBook DescriptionData scientists working on productionizing machine learning (ML) workloads f...

Learn how to apply powerful data analysis techniques with popular open source Python modulesKey Features\[\*\]Find, manipulate, and analyze your data using the Python 3.5 libraries\[\*\]Perform advanced, high-performance linear algebra and mathematical calculations with clean and efficient Python code\[\*\]An easy-to-follow guide with realistic examples that are frequently used in real-world data analysis projects.Book Description...

Publisher s Note: A new second edition, updated completely for pandas 1.x with additional chapters, has now been published. This edition from 2017 is outdated and is based on pandas 0.20. Over 95 hands-on recipes to leverage the power of pandas for efficient scientific computation and data analysisKey FeaturesUse the power of pandas 0.20 to solve most complex scientific computing problems with easeLeverage fast, robust data structures in pandas 0.20 to ...

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasksKey Features\[\*\] Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision\[\*\] Combine the power of Python, Keras, and TensorFlow to build deep learning models for object detection, image classification, similarity learning, image captioning, and more\[\*\] Includes tips on optimizing and improvi...

Integrate the power of R with the simplicity of Shiny to deliver cutting-edge analytics over the WebKey Features\[\*\] Use Shiny's built-in functions to produce engaging user interfaces, and integrate them into your own web pages\[\*\] Implement powerful user-contributed packages to access graphics from the web, make your own dashboards, use interactive maps, and more\[\*\] Extend Shiny using JavaScript and jQuery with minimal coding using this...

FPGAs (Field-Programmable Gate Arrays) can be found in applications such as smart phones, mp3 players, medical imaging devices, and for aerospace and defense technology. FPGAs consist of logic blocks and programmable interconnects. This allows an engineer to start with a blank slate and program the FPGA for a specific task, for instance, digital signal processing, or a specific device, for example, a software-defined radio. Due to the short time to market and ability to reprogram to fix bu...