Видавець: Packt Publishing
Giuseppe Bonaccorso, Armando Fandango, Rajalingappaa Shanmugamani
This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problemsThis Learning Path includes content from the following Packt products:• Mastering Machine Learning Algorithms by Giuseppe Bonaccorso• Mastering TensorFlow 1.x by Armando Fandango• Deep Learning for Computer Vision by Rajalingappaa Shanmugamani
Ashish Kumar, Joseph Babcock
Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form; it needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications. This book is your guide to getting started with predictive analytics using Python.You'll balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and NumPy. Through case studies and code examples using popular open-source Python libraries, this book illustrates the complete development process for analytic applications. Covering a wide range of algorithms for classification, regression, clustering, as well as cutting-edge techniques such as deep learning, this book illustrates explains how these methods work. You will learn to choose the right approach for your problem and how to develop engaging visualizations to bring to life the insights of predictive modeling.Finally, you will learn best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world. The course provides you with highly practical content from the following Packt books:1. Learning Predictive Analytics with Python2. Mastering Predictive Analytics with Python
Pushpak Dagade
If you want to find out how you can build a solid foundation in algorithmic trading using Python, this cookbook is here to help.Starting by setting up the Python environment for trading and connectivity with brokers, you’ll then learn the important aspects of financial markets. As you progress, you’ll learn to fetch financial instruments, query and calculate various types of candles and historical data, and finally, compute and plot technical indicators. Next, you’ll learn how to place various types of orders, such as regular, bracket, and cover orders, and understand their state transitions. Later chapters will cover backtesting, paper trading, and finally real trading for the algorithmic strategies that you've created. You’ll even understand how to automate trading and find the right strategy for making effective decisions that would otherwise be impossible for human traders.By the end of this book, you’ll be able to use Python libraries to conduct key tasks in the algorithmic trading ecosystem.Note: For demonstration, we're using Zerodha, an Indian Stock Market broker. If you're not an Indian resident, you won't be able to use Zerodha and therefore will not be able to test the examples directly. However, you can take inspiration from the book and apply the concepts across your preferred stock market broker of choice.
Aristides Bouras
This course is meticulously designed to take beginners on a journey through the fascinating world of Python programming and algorithmic thinking. The initial chapters lay a strong foundation, starting with the basics of how computers operate, moving into Python programming, and familiarizing learners with integrated development environments like IDLE and Visual Studio Code.Further, the course delves into essential programming constructs such as variables, constants, input/output handling, and operators. You'll gain practical experience with trace tables, sequence control structures, and decision control structures through comprehensive exercises and examples. The curriculum emphasizes hands-on learning with chapters dedicated to manipulating numbers, strings, and understanding complex mathematical expressions. By mastering these concepts, you'll be well-prepared to tackle more advanced topics.The final chapters introduce you to object-oriented programming and file manipulation, rounding out your skill set. Throughout the course, practical tips and tricks are provided to enhance your coding efficiency and problem-solving skills. By the end of this course, you will have a robust understanding of Python programming and the ability to apply algorithmic thinking to solve real-world problems.
Cuantum Technologies LLC
Embark on a transformative journey with this course designed to equip you with robust Python and SQL skills. Starting with an introduction to Python, you'll delve into fundamental building blocks, control flow, functions, and object-oriented programming. As you progress, you'll master data structures, file I/O, exception handling, and the Python Standard Library, ensuring a solid foundation in Python.The course then transitions to SQL, beginning with an introduction and covering basics, and proceeding to advanced querying techniques. You'll learn about database administration and how Python integrates seamlessly with SQL, enhancing your data manipulation capabilities. By combining Python with SQLAlchemy, you'll perform advanced database operations and execute complex data analysis tasks, preparing you for real-world challenges.By the end of this course, you will have developed the expertise to utilize Python and SQL for scientific computing, data analysis, and database management. This comprehensive learning path ensures you can tackle diverse projects, from basic scripting to sophisticated data operations, making you a valuable asset in the tech industry. You'll also gain hands-on experience with real-world datasets, enhancing your problem-solving skills and boosting your confidence.
Python API Development Fundamentals. Develop a full-stack web application with Python and Flask
Jack Chan, Ray Chung, Jack Huang
Python is a flexible language that can be used for much more than just script development. By knowing the Python RESTful APIs work, you can build a powerful backend for web applications and mobile applications using Python.You'll take your first steps by building a simple API and learning how the frontend web interface can communicate with the backend. You'll also learn how to serialize and deserialize objects using the marshmallow library. Then, you'll learn how to authenticate and authorize users using Flask-JWT. You'll also learn how to enhance your APIs by adding useful features, such as email, image upload, searching, and pagination. You'll wrap up the whole book by deploying your APIs to the cloud.By the end of this book, you'll have the confidence and skill to leverage the power of RESTful APIs and Python to build efficient web applications.
Jaime Buelta
Developing large-scale systems that continuously grow in scale and complexity requires a thorough understanding of how software projects should be implemented. Software developers, architects, and technical management teams rely on high-level software design patterns such as microservices architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD) to make their work easier.This book covers these proven architecture design patterns with a forward-looking approach to help Python developers manage application complexity—and get the most value out of their test suites.Starting with the initial stages of design, you will learn about the main blocks and mental flow to use at the start of a project. The book covers various architectural patterns like microservices, web services, and event-driven structures and how to choose the one best suited to your project. Establishing a foundation of required concepts, you will progress into development, debugging, and testing to produce high-quality code that is ready for deployment. You will learn about ongoing operations on how to continue the task after the system is deployed to end users, as the software development lifecycle is never finished.By the end of this Python book, you will have developed architectural thinking: a different way of approaching software design, including making changes to ongoing systems.
Dr. Joshua Eckroth
Artificial Intelligence (AI) is the newest technology that’s being employed among varied businesses, industries, and sectors. Python Artificial Intelligence Projects for Beginners demonstrates AI projects in Python, covering modern techniques that make up the world of Artificial Intelligence.This book begins with helping you to build your first prediction model using the popular Python library, scikit-learn. You will understand how to build a classifier using an effective machine learning technique, random forest, and decision trees. With exciting projects on predicting bird species, analyzing student performance data, song genre identification, and spam detection, you will learn the fundamentals and various algorithms and techniques that foster the development of these smart applications. In the concluding chapters, you will also understand deep learning and neural network mechanisms through these projects with the help of the Keras library.By the end of this book, you will be confident in building your own AI projects with Python and be ready to take on more advanced projects as you progress