CODE - AI Dynamics

Complete Machine Learning Package Update: MLOps Comprehensive Guide Coming Soon

By

–

27 January 2023 21h28

The next update on Complete Machine Learning Package will be a comprehensive guide on MLOps! Stay tuned, turn on notifications, and follow @Jeande_d for more cool learning resources and papers in the meantime. https://
nyandwi.com/machine_learni
ng_complete/
…

→ View original post on X — @jeande_d

27 January 2023

Weights & Biases: Essential MLOps Tool for Industry and Education

By

@jeande_d

–

27 January 2023 21h28

MLOps is hard but one of the reasons it's considered hard is the maturity of tools. Weights & Biases is one of the best tools we have to day in MLOps. Currently used in industries(ex: Open AI) and select tool in teaching MLOps in universities. Thanks to the team for this course!

→ View original post on X — @jeande_d

27 January 2023

MLOps Course: Building End-to-End ML Pipelines with Weights and Biases

By

@jeande_d

–

27 January 2023 21h28

ML lifecycle is very challenging but having an effective system and right tools can easy the process a little bit. In the new MLOps course from Weights and Biases(
@wandb
), you will learn how to build end-to-end ML pipelines. https://
wandb.courses/courses/effect
ive-mlops-model-development
…

→ View original post on X — @jeande_d

27 January 2023

New Free MLOps Course: End-to-End Model Development Pipeline

By

@jeande_d

–

27 January 2023 21h28

New MLOps FREE Course – Effective MLOps: Model Development from Weights and Biases There are lots of things involved in putting models into production. In this new course, you'll learn machine learning lifecycle and how to design end-to-end pipelines. https://
wandb.courses/courses/effect
ive-mlops-model-development
…

→ View original post on X — @jeande_d

27 January 2023

SQL Database Agent Optimization via Prompt Engineering

By

@langchain

–

27 January 2023 18h55

yes new ones! see the thread for an example of an agent optimized (via the prompt) for interacting with a sql db

→ View original post on X — @langchain

27 January 2023

Hugging Face Datasets Converter Transfer Kaggle Zenodo

By

@reach_vb

–

27 January 2023 18h32

This wouldn't have been possible without @_nateraw
's brilliant Hugging Face Datasets Converter Use it to transfer any dataset from Kaggle or Zenodo over to the Hub!

→ View original post on X — @reach_vb

27 January 2023

Dataset Preparation for AI Training in Two Lines Code

By

@reach_vb

–

27 January 2023 18h30

With just 2 lines of code the dataset would be ready for your training workflows!

→ View original post on X — @reach_vb

27 January 2023

Train Your Own MusicLM with MusicCaps Dataset

By

@reach_vb

–

27 January 2023 18h28

Want to train your own MusicLM? 🎶

The MusicCaps dataset is now on the 🤗Hub: https://t.co/JKrVYng9OY

The MusicCaps dataset contains 5,521 music examples, each of which is labeled with an English aspect list and a free text caption written by musicians. 🎸 pic.twitter.com/Byiy9r7hzs
— Vaibhav (VB) Srivastav (@reach_vb) 27 janvier 2023

Want to train your own MusicLM? The MusicCaps dataset is now on the Hub: https://
huggingface.co/datasets/googl
e/MusicCaps
… The MusicCaps dataset contains 5,521 music examples, each of which is labeled with an English aspect list and a free text caption written by musicians.

→ View original post on X — @reach_vb

27 January 2023

Serialized AI Agents: Should Tools Be Included Together?

By

@langchain

–

27 January 2023 18h15

will depend on what tools you use with it! these serialized agents do NOT include the specific tools (yet), they're just the agent logic and rely on users to pass intools do you think it would be more useful to have agents + tools serialized together?

→ View original post on X — @langchain

27 January 2023