Bøger af Ashwin Pajankar

Here is the perfect comprehensive guide for readers with basic to intermediate level knowledge of machine learning and deep learning. It introduces tools such as NumPy for numerical processing, Pandas for panel data analysis, Matplotlib for visualization, Scikit-learn for machine learning, and Pytorch for deep learning with Python. It also serves as a long-term reference manual for the practitioners who will find solutions to commonly occurring scenarios.The book is divided into three sections. The first section introduces you to number crunching and data analysis tools using Python with in-depth explanation on environment configuration, data loading, numerical processing, data analysis, and visualizations. The second section covers machine learning basics and Scikit-learn library. It also explains supervised learning, unsupervised learning, implementation, and classification of regression algorithms, and ensemble learning methods in an easy manner with theoretical and practical lessons. The third section explains complex neural network architectures with details on internal working and implementation of convolutional neural networks. The final chapter contains a detailed end-to-end solution with neural networks in Pytorch.After completing Hands-on Machine Learning with Python, you will be able to implement machine learning and neural network solutions and extend them to your advantage. What You'll LearnReview data structures in NumPy and Pandas Demonstrate machine learning techniques and algorithmUnderstand supervised learning and unsupervised learning Examine convolutional neural networks and Recurrent neural networksGet acquainted with scikit-learn and PyTorchPredict sequences in recurrent neural networks and long short term memory Who This Book Is ForData scientists, machine learning engineers, and software professionals with basic skills in Python programming.

Learn the core aspects of NumPy, Matplotlib, and Pandas, and use them to write programs with Python 3. This book focuses heavily on various data visualization techniques and will help you acquire expert-level knowledge of working with Matplotlib, a MATLAB-style plotting library for Python programming language that provides an object-oriented API for embedding plots into applications. You'll begin with an introduction to Python 3 and the scientific Python ecosystem. Next, you'll explore NumPy and ndarray data structures, creation routines, and data visualization. You'll examine useful concepts related to style sheets, legends, and layouts, followed by line, bar, and scatter plots. Chapters then cover recipes of histograms, contours, streamplots, and heatmaps, and how to visualize images and audio with pie and polar charts. Moving forward, you'll learn how to visualize with pcolor, pcolormesh, and colorbar, and how to visualize in 3D in Matplotlib, create simple animations, and embed Matplotlib with different frameworks. The concluding chapters cover how to visualize data with Pandas and Matplotlib, Seaborn, and how to work with the real-life data and visualize it. After reading Hands-on Matplotlib you'll be proficient with Matplotlib and able to comfortably work with ndarrays in NumPy and data frames in Pandas. What You'll LearnUnderstand Data Visualization and Python using MatplotlibReview the fundamental data structures in NumPy and Pandas Work with 3D plotting, visualizations, and animationsVisualize images and audio dataWho This Book Is ForData scientists, machine learning engineers and software professionals with basic programming skills.

Quickly start programming with Linux while learning the Raspberry Pi OS-the Linux distribution designed specifically for low-cost Raspberry Pis. This short guide reviews Linux commands, GUI, and shell scripting in a holistic manner by diving into both advanced and day-to-day tasks using the Raspberry Pi OS.You'll comfortably work with the Linux command prompt, and explore the RPi OS GUI and all its base applications. Then move into writing your own programs with shell-programming and using high-level languages such as C, C++, and Python 3. You'll also study hardware and GPIO programming. Use Python 3 for GPIO programming to drive LEDs and pushbuttons.Examples are written in Shell, C, C++, and Python 3. Graphical output is displayed in helpful screenshots that capture just what you'll see when working in this environment. All code examples are well tested on actual Raspberry Pi boards. After reading this book and following the examples, you'll be able to write programs for demonstration in your academic/industrial research work, business environment, or just your circle of friends for fun! What You'll LearnNavigate the core aspects of Linux and programming on a Linux platform Install Raspberry Pi OS on a Raspberry PiProgram in Shell, C, C++, and PythonRedirect Io and work with the crontabWho This Book Is ForLinux enthusiasts, software engineers, researchers, business analysts, and managers working with the low-cost Raspberry Pi.

Write your own Digital Image Processing programs with the use of pillow, scipy.ndimage and matplotlib in Python 3 with Raspberry Pi 3 as the hardware platform, including interfacing Raspberry Pi with image sensors. Master the use of the Pi camera and webcam. This quick-start guide gives working code examples and exercises.