Microsoft’s MetaOpt, AutoGen framework, RAGxplorer, FireLLaVA, Google DeepMind’s GenCast, FireAttention, Python RAG Framework for SQL Generation

Datapro Mini Library, Pecan’s Predictive GenAI, Mistral AI vs Meta, RLHF Tuning using Google's Vertex AI, Azure Data Factory, Mastering MongoDB 7.0 [View this email in your browser]( [Sign Up]( | [Advertise]( | [Archives]( January 26, 2024 | DataPro #78 👋 Hello {NAME}, Welcome to [DataPro Newsletter #78]( - your gateway to the frontier of data and AI! This edition is meticulously curated to elevate your expertise in the rapidly evolving world of data technologies. Let's dive into what makes this issue a must-read.  Key Highlights:  💎 Explore [Packt's New Year, New Data Upskilling program]( and discover the [Datapro Mini Library]( – an indispensable, user-friendly platform tailored for your data journey.   📀 Innovative Tools & Models:   - Meet [RAGxplorer]( and delve into [FireLLaVA]( - the groundbreaking, commercially permissive OSS LLaVA model.   - [Get acquainted with PythiaCHEM]( – a user-friendly machine learning toolkit revolutionizing chemistry.    - [Discover Marlin]( – A FP16xINT4 LLM Inference Kernel, achieving near-ideal ~4x speedups for enhanced efficiency.   - [Learn about FireAttention]( – Elevating Open Source Model serving speeds by 4x, with minimal trade-offs in quantization.  🌐 SQL Generation & Weather Forecasting:   - [Meet Vanna]( an innovative Python RAG Framework for SQL Generation.   - [Explore Google DeepMind’s GenCast]( for cutting-edge, diffusion-based ensemble forecasting in weather prediction.  ✨ On the Radar:   - Dive into [Pecan’s Predictive GenAI]( advanced [Git techniques]( and the transformative potential of [Generative AI in data visualization](   - Explore [No Code GenAI Agents]( [LLaVA as an alternative to GPT-4V]( and the open-source landscape with [Mistral AI vs Meta](   - Uncover the power of [AI for group interactions]( and strategies for optimizing [messy functions into production-ready code](  💰 GitHub Gems:   - Check out must-have GitHub repositories like [microsoft/autogen]( [Codium-ai/AlphaCodium]( [InstantID/InstantID]( [lucidrains/self-rewarding-lm-pytorch]( and [hkust-nlp/AgentBoard](   🏮 Tech Tidbits:   - Stay updated with AWS ML, including [enterprise-ready generative AI solutions on Amazon Bedrock and Weaviate vector database](   - Master ML with insights on [RLHF Tuning using Google's Vertex AI](   - Gain insights from [Microsoft Research on MetaOpt]( - a tool for enhancing heuristic performance.   📚 Packt Library Additions:   - Enhance your knowledge with new additions like, - [Math 0-1 - Matrix Calculus in Data Science and Machine Learning [Video] - By Lazy Programmer]( - [Azure Data Factory Cookbook - Second Edition - By Dmitry Foshin, Tonya Chernyshova, Dmitry Anoshin and 1 more]( - [Becoming a Data Analyst - By Kedeisha Bryan, Maaike van Putten]( - [Mastering MongoDB 7.0 - Fourth Edition - By Marko Aleksendrić , Arek Borucki, Leandro Domingues and 4 more](   DataPro Newsletter is not just a publication; it’s a comprehensive toolkit for anyone serious about mastering the ever-changing landscape of data and AI. Grab your copy and start transforming your data expertise today! 📥 Feedback on the Weekly Edition Take our weekly survey and get a free PDF copy of our best-selling book, "[Interactive Data Visualization with Python - Second Edition]( We appreciate your input and hope you enjoy the book! [Share your Feedback!]( Cheers,Merlyn ShelleyEditor-in-Chief, Packt [Sign Up]( | [Advertise]( | [Archives]( ✨ Packt's 2024 Specials ✨ Discover Packt's New Year, New Data Upskilling program, designed for data professionals. Gain a competitive edge in data science and analytics with expert-curated resources. Our goal? To help you seamlessly upgrade your skills in the most efficient way possible, enabling you to switch between topics without losing your stride.  [Introducing the Datapro Mini Library]( a smooth, user-friendly platform that you simply can't afford to miss. Here’s what our DataPro platform offers: - On-Demand Learning: Immerse yourself in Packt’s comprehensive data-based knowledge base, featuring hundreds of books, video courses, research papers, and articles. - Expert Problem Solving: Get bespoke solutions to your most challenging problems, directly from our vast network of data experts and authors. - Advanced Self-Assessment: Utilize our tools for skill gap analysis and progress tracking, pinpointing areas for improvement and tracking your learning journey. - Personalized DataPro Dashboard: Keep tabs on your activities, revisit recent learning sections, and receive tailored recommendations to align with your learning objectives. - Skill Gap Analysis: Deep dive into your SQL, R, Python, and other skills with detailed quizzes and personalized feedback.  The icing on the cake? Join the thriving community of more than 150 data/AI professionals in our [Discord channel](. Get exclusive access to our DataPro beta program, and even have a chance to win Amazon gift cards! All this is available for just $7.99 per month. Remember Benjamin Franklin's words, "An investment in knowledge pays the best interest." There’s no better time to invest in your professional growth than now. Don't miss this opportunity to power up your data journey. [Subscribe now and take the first step towards becoming a data mastermind!]( [Sign Up Here]( 🔰 GitHub Finds: Any of These Repos in Your Toolbox? 💎 [microsoft/autogen:]( AutoGen Studio is an AI app for creating, improving, and using AI agents to perform tasks quickly. It's based on the AutoGen framework. 💎 [Codium-ai/AlphaCodium:]( AlphaCodium is a new method for improving code generation by Large Language Models. It's effective on challenging code problems, enhancing accuracy and offering insights for broader code tasks. 💎 [InstantID/InstantID:]( InstantID is an advanced method for ID-preserving image generation using a single image, suitable for different downstream tasks, without requiring tuning. 💎 [lucidrains/self-rewarding-lm-pytorch:]( Implementing the training framework from [MetaAI's Self-Rewarding Language Model]( aiming to enhance language model performance through self-reward mechanisms. 💎 [hkust-nlp/AgentBoard:]( AgentBoard focuses on evaluating Large Language Models (LLMs) as versatile agents in diverse scenarios. It follows four principles: diverse tasks, multi-round interaction, partial observability, and analytical evaluation for comprehensive assessment. The evaluation platform provides insights into agent proficiency across various dimensions. 📚 Expert Insights from Packt Community 💎 [Math 0-1 - Matrix Calculus in Data Science and Machine Learning [Video] - By Lazy Programmer]( This video course provides a comprehensive journey through key concepts in mathematics for data science and machine learning. It covers matrix and vector derivatives, optimization techniques, and practical setup of essential tools. From foundational elements to advanced applications, this course equips you with the skills to excel in the field. Get started to embark on your path to success in data science and machine learning. 💎 [Azure Data Factory Cookbook - Second Edition - By Dmitry Foshin, Tonya Chernyshova, Dmitry Anoshin and 1 more]( The updated Azure Data Factory Cookbook guides you through creating and executing jobs in ADF, branching activities, scheduling pipelines, and integrating Azure services. Learn to harness cloud data warehousing, Azure Synapse Analytics, and Azure Data Lake Gen2 Storage for valuable insights. Troubleshoot errors, monitor pipelines, and design ETL pipelines efficiently. With practical recipes and new chapters, this book is essential for mastering ADF and optimizing your data projects. Get started now for successful data orchestration with ADF. 💎 [Becoming a Data Analyst - By Kedeisha Bryan, Maaike van Putten]( Here is a comprehensive book that guides you through the journey of becoming a proficient data analyst. It covers data collection, cleaning, analysis, modeling, and ethical considerations. With step-by-step instructions, real-world examples, and practical exercises, it equips you with the skills needed for success. Start your data analyst journey today with this essential guide.  💎 [Mastering MongoDB 7.0 - Fourth Edition - By Marko Aleksendrić , Arek Borucki, Leandro Domingues and 4 more]( This is a comprehensive guide to MongoDB, focusing on its latest version. It covers MongoDB's architecture, developer tools, advanced queries, and features like MongoDB Atlas and Atlas Vector Search. This book equips developers with the skills needed to build efficient, secure, and high-performing applications using MongoDB. Start mastering MongoDB 7.0 for modern web applications today! ⚡ Tech Tidbits: Stay Wired to the Latest Industry Buzz! AWS ML Made Easy 💎 [Build enterprise-ready generative AI solutions with Cohere foundation models in Amazon Bedrock and Weaviate vector database on AWS Marketplace:]( Generative AI, particularly using large language models (LLMs), is increasingly popular for enhancing business productivity and customer experience. However, LLMs' reliance on their training data can lead to inaccuracies. [Retrieval Augmented Generation (RAG)]( addresses this by supplementing LLMs with current, external information, improving accuracy. Ensuring data security, especially in regulated industries, is crucial. The post proposes a RAG pipeline using AI-native technology for building secure, accurate, and transparent AI applications, demonstrated using [Cohere’s models on Amazon Bedrock]( and [Weaviate’s database]( Mastering ML with Google 💎 [RLHF Tuning with Vertex AI:]( This blog discusses the use of foundation models, like large neural networks, for generative AI tasks across various domains. It highlights the importance of tuning these models using Reinforcement Learning from Human Feedback (RLHF) to align them with specific human preferences and values. The article also provides an example of how RLHF improved resume generation for the Recruit Group, demonstrating its potential to enhance model performance and automate content generation. Microsoft Research Insights 💎 [MetaOpt: Examining, explaining, and improving heuristic performance.](  MetaOpt, developed by Microsoft Research, is a tool for optimizing heuristic algorithms used in cloud operations like server assignments. It evaluates and refines these algorithms, ensuring efficient resource use and preventing over-provisioning. [MetaOpt]( uniquely analyzes and explains performance differences, making it easier for operators to improve algorithms. It's user-friendly and based on game theory, with plans for open-source release. [Check out the example use-cases here.](  [Email Forwarded? Join DataPro Here!]( 🔍 From Bits to BERT: Keeping Up with LLMs & GPTs 💎 [Meet RAGxplorer:]( RAGxplorer is an interactive AI tool that visualizes document chunks and queries in a high-dimensional space. It helps assess [RAG models' understanding]( handle various document formats, and reveal semantic relationships within documents, aiding researchers and developers in understanding and improving complex language models. 💎 [FireLLaVA - the first commercially permissive OSS LLaVA model:]( FireLLaVA, an open-source multi-modal model, bridges text and various data sources effectively. Vision-Language Models (VLMs) like LLaVA understand visual and text data, enhancing applications like marketing and chatbots. [FireLLaVA]( is commercially functional but may have limitations with multiple images and small text in input images. 💎 [PythiaCHEM : a user-friendly machine learning toolkit for chemistry.]( PythiaCHEM is a user-friendly machine learning toolkit for chemistry, addressing the need for small and sparse dataset solutions. It offers flexibility through [Jupyter Notebooks]( demonstrated in tasks involving anion transporters and amino acid synthesis, showcasing its versatility in chemistry domains. 💎 [Meet Marlin - A FP16xINT4 LLM Inference Kernel that can Achieve Near-Ideal ~4x Speedups up to Medium Batch Sizes of 16-32 Tokens:]( Marlin is a groundbreaking solution for speeding up large language models (LLMs) in computing. It efficiently handles larger data batches, optimizes GPU usage, and maintains near-ideal speedups, making it suitable for demanding tasks like serving large-scale applications and multi-inference schemes. [Marlin]( excels in performance metrics and is a reliable choice for consistent and fast LLM operations, pushing the boundaries of computational linguistics. 💎 [FireAttention — Serving Open Source Models 4x faster than vLLM by quantizing with ~no tradeoffs:]( Mixtral is an OSS model trained on trillions of tokens for ['mixture of experts']( (MoE), aiming to enhance training and inference speed. Fireworks AI introduces FireAttention for efficient MoE model serving with 4x speedup compared to alternatives, focusing on language understanding and latency metrics. 💎 [Meet Vanna: An Open-Source Python RAG (Retrieval-Augmented Generation) Framework for SQL Generation.]( Vanna, an open-source Python framework, simplifies SQL query generation, catering to users without deep SQL expertise. It employs a Retrieval-Augmented Generation (RAG) model, offering customization, versatility, high accuracy, and privacy while interacting with databases in an accessible manner. [Vanna]( is user-friendly and adaptable, making it a valuable tool for database queries.  💎 [Google DeepMind’s GenCast: Diffusion-based ensemble forecasting for medium-range weather.]( GenCast is an efficient machine learning model for probabilistic weather forecasting, outperforming traditional methods in skill and consistency. It provides accurate and fast predictions for various weather variables globally.  ✨ On the Radar: Catch Up on What's Fresh 💎 [Powering Up with Predictive GenAI:]( Pecan's Predictive GenAI combines predictive and generative AI for faster and more accessible predictive modeling. It simplifies the process from defining questions to SQL queries, [making it user-friendly for specific business needs](. It eliminates the need for coding and speeds up AI projects, enabling users to harness the power of AI for precise predictive models. [Try them out here!]( 💎 [10 Advanced Git Techniques:]( Learn 10 advanced Git techniques and shortcuts to enhance version control efficiency. Topics include one-line commit and amend commands, overriding remote history, reverting commits, utilizing Codespace, stashing changes, renaming branches, decorating logs, switching back branches, and copying remote changes. Gain proficiency in Git for smoother collaboration in data projects and software development. 💎 [How Generative AI Can Help You Improve Your Data Visualization Charts?]( This blog explores how to enhance data visualization charts using generative AI tools like GitHub Copilot, ChatGPT, and DALL-E. It covers creating a basic chart, adding annotations and images, and provides a practical use case with [Python Altair (Declarative Visualization in Python)]( 💎 [No Code GenAI Agents Workflow Orchestration: AutoGen Studio with Local Mistral AI model.]( Microsoft's AutoGen framework simplifies the development of multi-agent applications, particularly for coordinating large language models (LLM) agents. This article explores how [AutoGen Studio's no-code platform]( combines with the locally integrated Mistral AI model. The integration enables streamlined workflow orchestration, offering advantages like easy integration, customization, enhanced performance, data privacy, cost-efficiency, offline capabilities, and complex AI workflow construction through a user-friendly interface.  💎 [LLaVA: An open-source alternative to GPT-4V(ision).]( LLaVA is an open-source AI model that combines text and images for conversational tasks. It offers GPT-4-like capabilities but with simpler architecture and less data, making it faster and more cost-effective. You can use it online through a [web interface]( or install it on your device. It's versatile and can be used for various applications, as demonstrated with a chatbot example using HuggingFace libraries on Google Colab. 💎 [Mistral AI vs Meta: Open-source LLMs.]( Mistral AI, a European company, developed Mistral 7B, a smaller Large Language Model (LLM) with unique features like Group-Query Attention (GQA) and Sliding Window Attention (SWA) to improve LLM performance and reduce computational resources. They also created Mixtral 8x7B, which adds Sparse Mixture of Experts (SMoEs) to compete with larger LLMs. This article explores these innovations, compares Mistral 7B to Llama 2 7B, and Mixtral 8x7B to Llama 2 70B in terms of inference time, memory, and response quality. These comparisons use RAG systems and Amazon customer review datasets. 💎 [AI for Groups: Build a Multi-User Chat Assistant Using 7B-Class Models.]( The article discusses building a lightweight assistant for multi-user group conversations using open-source language models. It starts with a ChatGPT-3.5-Turbo baseline and aims to make the assistant respond appropriately. It explores the challenges and potential improvements, and then delves into fine-tuning open-source models for this purpose, showcasing dataset generation using Mixtral-8x7B-Instruct-v0.1. 💎 [5 Steps to Transform Messy Functions into Production-Ready Code:]( The article guides on improving a complex data science function used for handling missing values. It suggests making the function shorter, more adaptable, and reliable by breaking it into smaller parts, eliminating repetition, and enhancing its flexibility and error handling. This approach ensures the function can be easily used and modified for different datasets, improving code quality and maintainability. See you next time! On a scale of 1 to 10, how would you rate the practicality and value of today's newsletter issue for you? lowest [1]( [2]( [3]( [4]( [5]( [6]( [7]( [8]( [9]( [10]( highest Get in the Tech Loop! Subscribe to our newsletters covering Web & Mobile Dev, Cybersecurity, Cloud, Python, and more. Just hit that subscribe button! [Join the Tech Wave: Subscribe Today!]( Copyright (C) 2024 Packt Publishing,. All rights reserved.  As a GDPR-compliant company, we want you to know why you’re getting this email. The _datapro team, as a part of Packt Publishing, believes that you have a legitimate interest in our newsletter and its products. Our research shows that you,{EMAIL}, opted-in for email communication with Packt Publishing in the past and we think your previous interest warrants our appropriate communication. If you do not feel that you should have received this or are no longer interested in _datapro, you can opt-out of our emails by clicking the link below. Our mailing address is: Packt Publishing, Grosvenor House, 11 St Paul's Square,Birmingham, West Midlands, B3 1RB, United Kingdom [Add us to your address book]( Want to change how you receive these emails? You can [update your preferences]( or [unsubscribe](