End Jupyter Notebook In Terminal
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Building Conversational Generative AI Apps with Langchain and GPT: Develop End-to-End LLM-powered Conversational AI Apps with Python, LangChain, GPT and Google Colab
Author: Mugesh S.
language: en
Publisher: Orange Education Pvt Limited
Release Date: 2025-06-04
Transform Text into Intelligent Conversations with LangChain and GPT. Key Features● Build AI Chatbots with LangChain, Python and GPT models through hands-on guidance.● Master Advanced Techniques like RAG, document embedding, and LLM fine-tuning.● Deploy and Scale conversational AI systems for real-world applications. Book DescriptionConversational AI Apps are revolutionizing the way we interact with technology, enabling businesses and developers to create smarter, more intuitive applications that engage users in natural, meaningful ways. Building Conversational Generative AI Apps with LangChain and GPT is your ultimate guide to mastering AI-driven conversational systems. Starting with core concepts of generative AI and LLMs, you'll learn to build intelligent chatbots and virtual assistants, while exploring techniques like fine-tuning LLMs, retrieval-augmented generation (RAG), and document embedding. As you progress, you'll dive deeper into advanced topics such as vector databases and multimodal capabilities, enabling you to create highly accurate, context-aware AI agents. The book's step-by-step tutorials ensure that you develop practical skills in deploying and optimizing scalable conversational AI solutions. By the end, you'll be equipped to build AI apps that enhance customer engagement, automate workflows, and scale seamlessly. Unlock the potential of Building Conversational Generative AI Apps with LangChain and GPT and create next-gen AI applications today! What you will learn● Build and deploy AI-driven chatbots using LangChain and GPT models.● Implement advanced techniques like retrieval-augmented generation (RAG) for smarter responses.● Fine-tune LLMs for domain-specific conversational AI applications.● Leverage vector databases for efficient knowledge retrieval and enhanced chatbot performance.● Explore multimodal capabilities and document embedding for better context-aware responses.● Optimize and scale conversational AI systems for large-scale deployments.
Hacks, Leaks, and Revelations
Data-science investigations have brought journalism into the 21st century, and—guided by The Intercept’s infosec expert Micah Lee— this book is your blueprint for uncovering hidden secrets in hacked datasets. Unlock the internet’s treasure trove of public interest data with Hacks, Leaks, and Revelations by Micah Lee, an investigative reporter and security engineer. This hands-on guide blends real-world techniques for researching large datasets with lessons on coding, data authentication, and digital security. All of this is spiced up with gripping stories from the front lines of investigative journalism. Dive into exposed datasets from a wide array of sources: the FBI, the DHS, police intelligence agencies, extremist groups like the Oath Keepers, and even a Russian ransomware gang. Lee’s own in-depth case studies on disinformation-peddling pandemic profiteers and neo-Nazi chatrooms serve as blueprints for your research. Gain practical skills in searching massive troves of data for keywords like “antifa” and pinpointing documents with newsworthy revelations. Get a crash course in Python to automate the analysis of millions of files. You will also learn how to: Master encrypted messaging to safely communicate with whistleblowers. Secure datasets over encrypted channels using Signal, Tor Browser, OnionShare, and SecureDrop. Harvest data from the BlueLeaks collection of internal memos, financial records, and more from over 200 state, local, and federal agencies. Probe leaked email archives about offshore detention centers and the Heritage Foundation. Analyze metadata from videos of the January 6 attack on the US Capitol, sourced from the Parler social network. We live in an age where hacking and whistleblowing can unearth secrets that alter history. Hacks, Leaks, and Revelations is your toolkit for uncovering new stories and hidden truths. Crack open your laptop, plug in a hard drive, and get ready to change history.
Python: End-to-end Data Analysis
Author: Phuong Vothihong
language: en
Publisher: Packt Publishing Ltd
Release Date: 2017-05-31
Leverage the power of Python to clean, scrape, analyze, and visualize your data About This Book Clean, format, and explore your data using the popular Python libraries and get valuable insights from it Analyze big data sets; create attractive visualizations; manipulate and process various data types using NumPy, SciPy, and matplotlib; and more Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex data Who This Book Is For This course is for developers, analysts, and data scientists who want to learn data analysis from scratch. This course will provide you with a solid foundation from which to analyze data with varying complexity. A working knowledge of Python (and a strong interest in playing with your data) is recommended. What You Will Learn Understand the importance of data analysis and master its processing steps Get comfortable using Python and its associated data analysis libraries such as Pandas, NumPy, and SciPy Clean and transform your data and apply advanced statistical analysis to create attractive visualizations Analyze images and time series data Mine text and analyze social networks Perform web scraping and work with different databases, Hadoop, and Spark Use statistical models to discover patterns in data Detect similarities and differences in data with clustering Work with Jupyter Notebook to produce publication-ready figures to be included in reports In Detail Data analysis is the process of applying logical and analytical reasoning to study each component of data present in the system. Python is a multi-domain, high-level, programming language that offers a range of tools and libraries suitable for all purposes, it has slowly evolved as one of the primary languages for data science. Have you ever imagined becoming an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? If yes, look no further, this is the course you need! In this course, we will get you started with Python data analysis by introducing the basics of data analysis and supported Python libraries such as matplotlib, NumPy, and pandas. Create visualizations by choosing color maps, different shapes, sizes, and palettes then delve into statistical data analysis using distribution algorithms and correlations. You'll then find your way around different data and numerical problems, get to grips with Spark and HDFS, and set up migration scripts for web mining. You'll be able to quickly and accurately perform hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making. Finally, you will delve into advanced techniques such as performing regression, quantifying cause and effect using Bayesian methods, and discovering how to use Python's tools for supervised machine learning. The course provides you with highly practical content explaining data analysis with Python, from the following Packt books: Getting Started with Python Data Analysis. Python Data Analysis Cookbook. Mastering Python Data Analysis. By the end of this course, you will have all the knowledge you need to analyze your data with varying complexity levels, and turn it into actionable insights. Style and approach Learn Python data analysis using engaging examples and fun exercises, and with a gentle and friendly but comprehensive "learn-by-doing" approach. It offers you a useful way of analyzing the data that's specific to this course, but that can also be applied to any other data. This course is designed to be both a guide and a reference for moving beyond the basics of data analysis.