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- Python Weekly (Issue 592 March 16 2023)
Python Weekly (Issue 592 March 16 2023)
Python Weekly - Issue 592
Python Weekly
Welcome to issue 592 of Python Weekly. Let's get straight to the links this week.
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A weekly newsletter featuring the best hand curated news, articles, tutorials, talks, tools and libraries etc for programmers.
Articles, Tutorials and Talks
This video dives into the GRASP design principles and explore why they matter when designing software systems. By understanding these principles, you'll be able to write better code that's easier to maintain and extend.
After needing to do a deep dive on the venv module (which I will explain later in this blog post as to why), I thought I would explain how virtual environments work to help demystify them.
This post is part-1 of the two series blog posts on CLIP. In this post, we present an Introduction to CLIP in an easy to digest manner. We also compare CLIP to other research papers and look at the background and inspiration behind CLIP.
Part-2 - In this part, we present the PyTorch code behind CLIP for model building and training. This blog post is in itself a working Jupyter Notebook.
In this tutorial, you'll learn how to use OpenAI's API with Python to generate, edit, and vary images using natural language prompts.
We’re seeing successively difficult problems getting solved thanks to machine learning (ML) models. In this article, you’ll see An overview of Document AI, Practical and visual examples and A document processing demo (source code included)
Django signals provide a powerful way to trigger actions when specific events occur, but are they asynchronous or synchronous? In this article, we'll explore the answer to this question and discuss the pros and cons of using Django signals in your web applications.
In this video, we explore how to securely manage and use secrets like API keys, passwords, credential pairs, and other sensitive information in python. We run through the basics of using environment variables and move on to more advanced scenarios such as managing different secrets for multiple environments.
Learn keyboard shortcuts that will make you a more efficient and productive Python programmer with VS Code.
Interesting Projects, Tools and Libraries
Visual ChatGPT connects ChatGPT and a series of Visual Foundation Models to enable sending and receiving images during chatting.
AgentChain uses Large Language Models (LLMs) for planning and orchestrating multiple Agents or Large Models (LMs) for accomplishing sophisticated tasks. AgentChain is fully multimodal: it accepts text, image, audio, tabular data as input and output.
Guardrails is an open-source Python package for specifying structure and type, validating and correcting the outputs of large language models (LLMs).
Code and documentation to train Stanford's Alpaca models, and generate the data.
Identify unused dependencies and avoid a bloated virtual environment.
Ethical hacking, made easy.
Basaran is an open-source alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models.
OpenChatKit provides a powerful, open-source base to create both specialized and general purpose chatbots for various applications. The kit includes an instruction-tuned 20 billion parameter language model, a 6 billion parameter moderation model, and an extensible retrieval system for including up-to-date responses from custom repositories.
Your Personal Multilingual AI Translator.
An open source Python toolkit for graph-relational data across space and time.
FastKafka is a powerful and easy-to-use Python library for building asynchronous web services that interact with Kafka topics. Built on top of Pydantic, AIOKafka and AsyncAPI, FastKafka simplifies the process of writing producers and consumers for Kafka topics.
A functional training loops library for JAX.
Upcoming Events and Webinars
There will be following talks
Using Machine Learning with Python for Making Staffing decisions
Paths for Contributing to PyData Open Source Projects
There will be following talks
Creating a graph database using Python
How to build an air quality dashboard using PySpark, Python and AWS
There will be following talks
Achieving High Business Demands with State-of-the-Art Multihorizon Heat Predictions: A Journey from ARIMA Models to Temporal Fusion Transformers at Iqony
Apache Spark vs. cloud native SQL
There will be following talks
To recall or not to recall?: Training AI to read mammograms
Artiman or Huficial Intelligence - it's perplexing
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