Deep Dive Python Programming
Deep Dive Python Programming
About the Bundle
Unleash the full potential of Python in the realms of network automation and artificial intelligence with this meticulously curated bundle. "Mastering Python Network Automation" is your gateway to automating network tasks with Python. Tim Peters guides you through the nuances of leveraging Python for network configuration, management, and automation tasks, making it an indispensable resource for network engineers aiming to enhance their workflow efficiency.
Complementing this, "Python AI Programming" by Patrick J offers a profound exploration into the use of Python for AI development. From fundamental concepts to advanced machine learning techniques, this book equips you with the knowledge to implement AI solutions effectively. It's designed for programmers and data scientists who wish to broaden their expertise in AI technologies.
Together, these books provide a robust foundation in Python programming, covering both the practical aspects of network automation and the theoretical underpinnings of AI. This bundle is ideal for those looking to master Python for professional growth in fields like network engineering, data science, and AI development, blending practical applications with cutting-edge technology insights.
About the Books
Mastering Python Network Automation
Automating Container Orchestration, Configuration, and Networking with Terraform, Calico, HAProxy, and Istio
With "Mastering Python Network Automation," you can streamline container orchestration, configuration management, and resilient networking with Python and its libraries, allowing you to emerge as a skilled network engineer or a strong DevOps professional.
From the ground up, this guide walks readers through setting up a network automation lab using the NS3 network simulator and Python programming. This includes the installation of NS3, as well as python libraries like nornir, paramiko, netmiko, and PyEZ, as well as the configuration of ports, hosts, and servers. This book will teach you the skills to become a proficient automation developer who can test and fix any bugs in automation scripts. This book examines the emergence of the service mesh as a solution to the problems associated with service-to-service communication over time.
This book walks you through automating various container-related tasks in Python and its libraries, including container orchestration, service discovery, load balancing, container storage management, container performance monitoring, and rolling updates. Calico and Istio are two well-known service mesh tools, and you'll find out how to set them up and configure them to manage traffic routing, security, and monitoring. Additional topics covered in this book include the automation of network policies, the routing of workloads, and the collection and tracking of metrics, logs, and traces. You'll also pick up some tips and tricks for collecting and visualizing Istio metrics with the help of tools like Grafana.
Key Learnings
- Use of Istio for cluster traffic management, traffic routing, and service mesh
- implementation.
- Utilizing Cilium and Calico to solve pod networking and automate network policy
- and workload routing.
- Monitoring and managing Kubernetes clusters with etcd and HAProxy load
- balancers and container storage.
- Establishing network automation lab with tools like NS3 emulator, Python, Virtual
- Environment, and VS Code.
- Establishing connectivity between hosts, port connectivity, SSH connectivity,
- python libraries, NS3, and network encryption.
Table of Content
- Python Essentials for Networks
- File Handling and Modules in Python
- Preparing Network Automation Lab
- Configuring Libraries and Lab Components
- Code, Test & Validate Network Automation
- Automation of Configuration Management
- Managing Docker and Container Networks
- Orchestrating Container & Workloads
- Pod Networking
- Implementing Service Mesh
Python AI Programming
Navigating fundamentals of ML, deep learning, NLP, and reinforcement learning in practice
This book aspires young graduates and programmers to become AI engineers and enter the world of artificial intelligence by combining powerful Python programming with artificial intelligence. Beginning with the fundamentals of Python programming, the book gradually progresses to machine learning, where readers learn to implement Python in developing predictive models.
The book provides a clear and accessible explanation of machine learning, incorporating practical examples and exercises that strengthen understanding. We go deep into deep learning, another vital component of AI. Readers gain a thorough understanding of how Python's frameworks and libraries can be used to create sophisticated neural networks and algorithms, which are required for tasks such as image and speech recognition. Natural Language Processing is also covered in the book, with fundamental concepts and techniques for interpreting and generating human-like language covered.
The book's focus on computer vision and reinforcement learning is distinctive, presenting these cutting-edge AI fields in an approachable manner. Readers will learn how to use Python's intuitive programming paradigm to create systems that interpret visual data and make intelligent decisions based on environmental interactions. The book focuses on ethical AI development and responsible programming, emphasizing the importance of developing AI that is fair, transparent, and accountable.
Each chapter is designed to improve learning by including practical examples, case studies, and exercises that provide hands-on experience. This book is an excellent starting point for anyone interested in becoming an AI engineer, providing the necessary foundational knowledge and skills to delve into the fascinating world of artificial intelligence.
Key Learnings
- Explore Python basics and AI integration for real-world application and career advancement.
- Experience the power of Python in AI with practical machine learning techniques.
- Practice Python's deep learning tools for innovative AI solution development.
- Dive into NLP with Python to revolutionize data interpretation and communication strategies.
- Simple yet practical understanding of reinforcement learning for strategic AI decision making.
- Uncover ethical AI development and frameworks, and concepts of responsible and trustworthy AI.
- Harness Python's capabilities for creating AI applications with a focus on fairness and bias.
Table of Content
- Introduction to Artificial Intelligence
- Python for AI
- Data as Fuel for AI
- Machine Learning Foundation
- Essentials of Deep Learning
- NLP and Computer Vision
- Hands-on Reinforcement Learning
- Ethics to AI
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