libraries

Use these frameworks to empower your machine-learning work Link

Large Language Models(LLM) have taken the NLP community AI community the Whole World by storm. Here is a curated list of papers about large language models, especially relating to ChatGPT. It also contains frameworks for LLM training, tools to deploy LLM, courses and tutorials about LLM and all publicly available LLM checkpoints and APIs. Link

Curated list of best courses, books, resources on large language model Link

common packages used in python while working as Data Engineers Link

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. Link

There is a proverb “You don’t have to reinvent the wheel”. Libraries are the best example of that. It helps you to write complex and time-consuming functionality in an easy way. According to me, a good project uses some of the best libraries available. Link

Power up your Python development Link

Daft is currently in its Alpha release phase - please expect bugs and rapid improvements to the project. We welcome user feedback/feature requests in our Discussions forums. Link

It’s a general purpose micro-framework for creating dataflows from python functions! Link

Hypothesis is a Python library for creating unit tests which are simpler to write and more powerful when run, finding edge cases in your code you wouldn’t have thought to look for. It is stable, powerful and easy to add to any existing test suite. Link

Modin is a drop-in replacement for pandas. While pandas is single-threaded, Modin lets you instantly speed up your workflows by scaling pandas so it uses all of your cores. Modin works especially well on larger datasets, where pandas becomes painfully slow or runs out of memory. Link

PyXAB is a Python open-source library for X-armed bandit algorithms, a prestigious set of optimizers for online black-box optimization, i.e., optimize an objective without gradients, also known as the continuous-arm bandit (CAB), Lipschitz bandit, global optimization (GO) and bandit-based black-box optimization problems. Link

TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale. Link

scales from a single function to thousands of distributed tasks. syncs your local code and libraries for a faster, easier iteration loop. Edit your code and rerun your analysis without worrying about building packages or Docker images. optimizes for cost, choosing the cheapest instance types and turning them off when they’re no longer needed. Link

This article proposes an elegant way to build generator pipelines Link