“…The book concludes with an overview of big data analytics, R and Python essentials for analytics including libraries such as pandas and NumPy. Upon completing this book, you will understand how to improve business outcomes by leveraging R and Python for data analytics. …”

“…He's been working with Spark since version 0.6 and is co-author of the book "Learning PySpark" (Packt Publishing). Denny has a Master's degree in Biomedical Informatics from Oregon Health and Sciences University…”

“…Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming, including Python, TensorFlow, Keras, and PyTorch. AI Crash Course teaches everyone to build an AI to work in their applications. …”

“…Install and run the right version of Python for your operating system Store, manipulate, reformat, combine, and organize information Create logic to control how programs run and what they do Interact with users or other programs, wherever they are Save time and improve reliability by creating reusable functions Master Python data types: numbers, text, lists, and dictionaries Write object-oriented programs that work better and are easier to improve Expand Python classes to make them even more powerful Use third-party modules to perform complex tasks without writing new code Split programs to make them more maintainable and reusable Clearly document your code so others can work with it Store data in SQLite databases, write queries, and share data via JSON Simplify Python web development with the Flask framework Quickly program Python games with PyGame Avoid, troubleshoot, and fix problems with your code…”

“…Aron is one of the lead developers of PyClaw, an open-source, Python-based toolkit for modeling wave propagation at large scale. …”

“…You will also learn the NumPy library used for numerical and scientific computation. …”

“…Auflage: Sie erstellen das neuronale Netz abschließend mit PyTorch und überführen es damit in ein typisches professionelles Szenario…”

“…Prerequisites: Working knowledge of Python Data science experience a plus but not necessary Familiarity with NumPy a plus but not necessary Basics of machine learning a plus but not necessary An understanding of statistics and mathematics a plus but not necessary Familiarity with deep learning a plus but not necessary Recommended follow-up Learning TensorFlow (book) TensorFlow for Deep Learning (book) Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 3rd Edition (book) Designing Data-Intensive Applications (book) Fundamentals of Data Engineering (book)…”

“…Throughout the course, we will explore the most essential Python features: Basics of Python programming – expressions, variables, and printing output Python operators – the Python assignment operator, relational and logical operators, and short circuit operators Python conditionals and if statements Methods – parameters, arguments, and return values Object-oriented programming – classes and objects Encapsulation, inheritance, and abstract classes Python data structures in-depth – lists, sets, dictionaries, and tuples Conditionals – if/else statements and nested if/else Loops – for loops, while loops, break, and continue The mutability and immutability of Python’s basic types Built-in and user-defined modules Errors and exception handling – try, except, else, and finally Custom exceptions – raising exceptions and creating and raising a custom exception Data analysis with Pandas Face recognition with OpenCV Building a GUI application with Tkinter An automated Twitter bot with Tweepy Understanding the basics of databases and working with SQLite 3 Five projects with OpenCV, pandas, PyTube, Tkinter, Tweepy, and more After completing this course, you will be ready to work as an intern, fresher, or freelancer, and you will also be able to implement everything yourself! …”

“…Get your Raspberry Pi and choose the right low-cost peripherals Set up Raspian Linux and the Python programming environment Learn Python basics, including arithmetic and structured commands Master Python 3 lists, tuples, dictionaries, sets, strings, files, and modules Reuse the same Python code in multiple locations with functions Manipulate string data efficiently with regular expressions Practice simple object-oriented programming techniques Use exception handling to make your code more reliable Program modern graphical user interfaces with Raspberry Pi and OpenGL Create Raspberry Pi games with the PyGame library Learn network, web, and database techniques you can also use in business software Write Python scripts that send email Interact with other devices through Raspberry Pi’s GPIO interface Walk through example Raspberry Pi projects that inspire you to do even more…”

“…As you advance, you will gain an in-depth understanding of Python libraries such as NumPy and pandas for analyzing financial datasets, and explore Matplotlib, statsmodels, and scikit-learn libraries for advanced analytics. …”

“…Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems What you will learn Use machine learning algorithms with complex datasets to implement cybersecurity concepts Implement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problems Learn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDA Understand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimes Use TensorFlow in the cybersecurity domain and implement real-world examples Learn how machine learning and Python can be used in complex cyber issues Who this book is for This book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. …”

“…Readers will need to have a working knowledge of Python, and some experience of SQL in PySpark and Spark SQL is beneficial…”

“…Topics include: The details of object creation and naming Namespace changing features including assignment, del, import, function definition, class definition, and decorators Disassembling CPython bytecode to understand some Python features Iterables, iterators, and the iterator protocol How to use generators to make your code easier to read and understand Monkey patching classes, creating classes dynamically, and how bound methods work Using special methods in classes Several ways other than classes to bind data with functions Python 3 features such as tuple assignment with extended iterable unpacking and keyword-only function arguments Stuart Williams has been teaching Python for over a decade to audiences as diverse as adults in industry and at PyCon, students in university, high school students at a week-long Python summer camp, and grade school students learning Raspberry Pi. …”

“…Once you've explored a few leading problem-solving ML algorithms, this book will help you tackle data management and get the most out of ML libraries such as TensorFlow and PyTorch. Using open source technology such as Kubernetes/Kubeflow to build a data science environment and ML pipelines will be covered next, before moving on to building an enterprise ML architecture using Amazon Web Services (AWS). …”

“…Coverage includes Developing in Python using procedural, objectoriented, and functional programming paradigms Creating custom packages and modules Writing and reading binary, text, and XML files, including optional compression, random access, and text and XML parsing Leveraging advanced data types, collections, control structures, and functions Spreading program workloads across multiple processes and threads Programming SQL databases and key—value DBM files Debugging techniques–and using Test Driven Development to avoid bugs in the first place Utilizing Python’s regular expression mini-language and module Parsing techniques, including how to use the third-party PyParsing and PLY modules Building usable, efficient, GUI-based applications Advanced programming techniques, including generators, function and class decorators, context managers, descriptors, abstract base classes, metaclasses, coroutines, and more Programming in Python 3, Second Edition, serves as both tutorial and language reference. …”

“…To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. …”

“…Coverage includes Leveraging Python’s most effective creational, structural, and behavioral design patterns Supporting concurrency with Python’s multiprocessing, threading, and concurrent.futures modules Avoiding concurrency problems using thread-safe queues and futures rather than fragile locks Simplifying networking with high-level modules, including xmlrpclib and RPyC Accelerating Python code with Cython, C-based Python modules, profiling, and other techniques Creating modern-looking GUI applications with Tkinter Leveraging today’s powerful graphics hardware via the OpenGL API using pyglet and PyOpenGL…”

“…You'll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod. …”

“…You will probably want a good IDE for python, two of the most popular ones are "Visual Studio Code": https://code.visualstudio.com/ and "PyCharm": https://www.jetbrains.com/pycharm/ …”