Welcome to this week's edition of our newsletter! We've got a mix of educational and exciting content to share with you today, all links included for your reference to dive right in.
Have you ever wondered how machine learning came to be? Our first link takes you on the journey of ML from Zero, covering its evolution from its early roots to the sophisticated technology we know today. This is a great read for anyone interested in the history of computer science and how ML has become such a fundamental component of many industries.
Next up, we have a fun challenge for all the coding enthusiasts out there! Have you created your first bot yet? Fear not, we have just the thing to get you started. In Hello World challenges: creating my first bot with Python RPA using BotCity, follow along with step-by-step instructions to create your very own Python bot using BotCity. This comprehensive guide will have you building your own automated bots in no time!
If you're a fan of language models, then you'll want to check out our next two links. Delve into the fascinating world of instruction-following LLMs (language learning models) with WizardLM and WizardCoder, powered by Evol-Instruct. These models are designed to interpret and follow instructions, and this technology has endless applications from programming to language translation.
For anyone new to Python programming, our fourth link will come in handy. Our markdown-style link takes you to Python Syntax: The Lazy Guide for Beginners, a comprehensive guide covering the basics of Python syntax. This guide is perfect if you're just starting your journey into Python or if you need a quick refresher on the basics.
Finally, if you've ever wondered how hackers manage to break into WiFi networks, then our last link is for you. WiFi Hacking: A Comprehensive Guide takes you through the ins and outs of WiFi hacking. Learn how to identify vulnerabilities and take advantage of them, as well as the precautions you can take to secure your network.
We hope you enjoy this week's newsletter and find these links as fascinating as we did. Happy reading!
Updates From The Python Blog
- Python 3.12.0 beta 3 released - Tuesday, June 20, 2023
Our Article Picks
- Maksim Karyagin: Statistics: Сrash Course for Data Science. Part l
- Philip John Basile: MicroPython 101 IoT Basics
- Akshay Ballal: Building a Vision Transformer from Scratch in PyTorch 🔥
- Aditi Sharma: MongoDB: Unlocking the Power of Data Storage and Retrieval
- Morganna: Os desafios do Hello World: criando meu primeiro bot com Python RPA utilizando BotCity
- Morganna: Hello World challenges: creating my first bot with Python RPA using BotCity
- Code White Dev: The journey of ML from Zero.
- Santhosh Balasa: Decorators in Rust
- Scofield Idehen: Python Syntax: The Lazy Guide for Beginners
- Scofield Idehen: WiFi Hacking: A Comprehensive Guide
- Santhosh Balasa: Rust: Embrace the Pythonic Flair with F-String Style!
- Mwenda Harun Mbaabu: Demystifying the Data Product Lifecycle: From Inception to Retirement
- Lionel Tchami: Never Fill Out Another Boring Online Form. Use Python to make it automatic!
- Shittu Olumide: How can I set max_split_size_mb to avoid fragmentation in Pytorch?
- Rachit Khurana: Let's Learn Django #5 Django Template
- Lionel Tchami: 8 Open-Source Data Analysis Projects for Your Resume (2023)
- Shittu Olumide: Memory Management using PYTORCH_CUDA_ALLOC_CONF
- HostyCord: HostyCord: The Free Hosting Platform Empowering Your Online Projects
- Adheeban Manoharan: I built a tool that creates and posts AI content to social media automatically
- Vishnu Sivan: Pandas AI: Supercharging data analysis with generative AI
- Mihai-Adrian Andrei: Building a FastAPI Application and Deploying it with Vercel
- EzeanaMichael: How to build a simple Machine Learning Classification Model.
- stelin: Openjob: best distributed task scheduling framework
- AtulKushwaha: creating own RANDOM number generator
- Shilleh: How to Transfer Data/Files from Raspberry Pi Pico to Local Computer (Programmatically)
- john wirt: Basic Weekly Payroll Calculator
- Vishnu Sivan: Revolutionizing NLP Summarization with LangChain: Overcoming Challenges of Large Document Processing and Information Fusion
- Angela Palaszewski: Make a Fun CLI Project
- jmau111⚡⚡⚡: Python: async programming
- Shittu Olumide: Copy.deepcopy() vs clone() in Pytorch
- John Vester: Building Better dapps with Infura’s Polygon WebSocket
- Philip Case: Snapshot of the Most Popular Programming Languages in 2023
- Maksim Karyagin: Statistics: Сrash Course for Data Science. Part 2
- ashishnimrot: Node.js vs. Java/PHP/Python
- Jacqueline Wisdom: Intro to Python
- Marcos Silva: A Comprehensive Overview of the Python PostgreSQL Library
- Sachin: Read And Write ZIP Files Without Extracting Using zipfile Module
- Raymond Lee: The Code of Relationships: Applying Programming Principles to Love and Connection
- Sheriff S: Getting Started with Pygame: Create Your Own Games in Python!
- SnykSec: Research with Snyk and Redhunt Labs: Scanning the top 1000 orgs on GitHub
- Ankit malik: Difference Among Casings: Snake Case VS Camel Case VS Pascal Case VS Kebab Case
- Galopin: My first python program c:
- joshin4colours: Taking The Scenic Route With Python Test Automation
- Retiago Drago: ⭐ Beyond Stars: The 'Helpful Rating System' 👍 Outshines Traditional 5-Star Reviews!
- Michael Neo: My first Python terminal game...
- SnykSec: Fixing half a million security vulnerabilities
- Akshat Jain: Agent Instructions: Autonomous AI Agent Trajectory Fine-Tuning
- Nga Mai: [ Remote] Reco is hiring Python Flask Techlead
- Celso Jr: Building A Python Script For Natural Language Q&A In The Console For Free Using A LLaMA Model
- Syed Muhammad Ali Raza: Unlocking the Power of YOLO v4
- Sanjay Khati Chhetri: A Comprehensive Guide to Variable Scope in Python
- Whitehackerneth: Why did the two Java methods get a divorce?
- HRmemon: Maximum Strength of a Group of Numbers (beats 97.26% in runtime)
- Miracle Watt: Miracle Watt - Results, Benefits, Pros, Cons, Uses, Scam Or Legit?
- Makaela King: Code Review - Documatic
- Irishgeoff11: Guide to dynamic programming
- Sanjay Khati Chhetri: operators in python
- Asmae El-Ghezzaz: 📢 Elevate Your Data Science Projects with ReactPy: A Python Framework for Interactive Applications! 🚀
Our Repo Picks
- AntonOsika/gpt-engineer (Python): Specify what you want it to build, the AI asks for clarification, and then builds it.
- bentoml/OpenLLM (Python): An open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease.
- nlpxucan/WizardLM (Python): Family of instruction-following LLMs powered by Evol-Instruct: WizardLM, WizardCoder
- hiyouga/LLaMA-Efficient-Tuning (Python): Fine-tuning LLaMA with PEFT (PT+SFT+RLHF with QLoRA)
- baichuan-inc/baichuan-7B (Python): A large-scale 7B pretraining language model developed by BaiChuan-Inc.
- unifyai/ivy (Python): Unified AI
- Lightning-AI/lit-gpt (Python): Implementation of Falcon, StableLM, Pythia, INCITE language models based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.
- alejandro-ao/ask-multiple-pdfs (Python): A Langchain app that allows you to chat with multiple PDFs
- OptimalScale/LMFlow (Python): An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Model for All.
- h2oai/h2ogpt (Python): Join us at H2O.ai to make the world's best open-source GPT with document and image Q&A, 100% private chat, no data leaks, Apache 2.0 https://arxiv.org/pdf/2306.08161.pdf
- scikit-learn/scikit-learn (Python): scikit-learn: machine learning in Python
- h2oai/h2o-llmstudio (Python): H2O LLM Studio - a framework and no-code GUI for fine-tuning LLMs
- facebookresearch/ijepa (Python): Official codebase for I-JEPA, the Image-based Joint-Embedding Predictive Architecture. First outlined in the CVPR paper, "Self-supervised learning from images with a joint-embedding predictive architecture."
- open-mmlab/mmagic (Python): OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc.
- minimaxir/simpleaichat (Python): Python package for easily interfacing with chat apps, with robust features and minimal code complexity.
- THUDM/WebGLM (Python): WebGLM: An Efficient Web-enhanced Question Answering System (KDD 2023)
- geohot/tinygrad (Python): You like pytorch? You like micrograd? You love tinygrad! ❤️
- Deci-AI/super-gradients (Python): Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
- oobabooga/text-generation-webui (Python): A gradio web UI for running Large Language Models like LLaMA, llama.cpp, GPT-J, Pythia, OPT, and GALACTICA.
- ruoccofabrizio/azure-open-ai-embeddings-qna (Python): A simple web application for a OpenAI-enabled document search. This repo uses Azure OpenAI Service for creating embeddings vectors from documents. For answering the question of a user, it retrieves the most relevant document and then uses GPT-3, GPT-3.5 or GPT-4 to extract the matching answer for the question.
- donnemartin/system-design-primer (Python): Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
- hwchase17/langchain (Python): ⚡ Building applications with LLMs through composability ⚡
- lss233/chatgpt-mirai-qq-bot (Python): 🚀 一键部署！真正的 AI 聊天机器人！支持 ChatGPT、文心一言、讯飞星火、Bing、Bard、ChatGLM、POE，多账号，人设调教，虚拟女仆、图片渲染、语音发送 | 支持 QQ、Telegram、Discord、微信 等平台
- KoboldAI/KoboldAI-Client (Python): undefined
- iam-veeramalla/Jenkins-Zero-To-Hero (Python): Install Jenkins, configure Docker as slave, set up cicd, deploy applications to k8s using Argo CD in GitOps way.
The Last Week In Python is a weekly roundup for all things Python! Follow me on Twitter for more projects @dennisokeeffe92.
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