https://www.quantamagazine.org/researchers-discover-a-more-flexible-approach-to-machine-learning-20230207/
#machinelearning
@kdnuggets @datasciencechats

https://www.kaggle.com/discussions/product-feedback/391200
#kaggle
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https://openai.com/blog/introducing-chatgpt-and-whisper-apis
#artificialintelligence #chatgpt
@kdnuggets @datasciencechats

45M datasets from more than 13k websites. Dataset Search a dedicated search engine for datasets
@kdnuggets @datasciencechats
#datasets
https://ai.googleblog.com/2023/02/datasets-at-your-fingertips-in-google.html

https://www.twilio.com/blog/2018/06/data-science-linear-algebra-python-scipy-numpy.html
#linearalgebra #python
@kdnuggets @datasciencechats

First thing if you are a beginner and have decided you want to learn Data Science then know that it is a journey (6 months - 1 year at least) and not a 1 month thing where u do some courses and you are a data scientist. There are different fields in Data Science that you have to first get familiar and strong in basics as well as do hands-on to get the abilities that are required to function in a full time job opportunity. Then further delve into advanced implementations.

There are plenty of roadmaps and online content both paid and free that you can follow. In a nutshell. A few essential things that will be necessary and in no particular order that will at least get your data science journey started are below:

Basic Statistics, Linear Algebra, calculus, probability
Programming language (R or Python) - Preferably Python if you rather want to later on move into a developer role instead of sticking to data science.
Machine Learning - All of the above will be used here to implement machine learning concepts.
Data Visualisation - again it could be simple excel or via r/python libraries or tools like Tableau,PowerBI etc.

This can be overwhelming but again its just an indication of what lies ahead. So most important thing is to just START instead of just contemplating the best way to go about this. Since lot of things can be learnt independently as well in no particular order.

You can use the below Sources to prepare your own roadmap:
@coursenuggets - some free courses from here
@kdnuggets - check & search in this channel with #beginner
Python - https://bit.ly/38vaKjc
Kaggle - https://www.kaggle.com/learn
Udemy - https://bit.ly/3wmpvjH
Coursera - https://bit.ly/3o1R7ab

https://ai.facebook.com/blog/segment-anything-foundation-model-image-segmentation/
#ai #imagesegmentation
@kdnuggets @datasciencechats

A Free course designed for people with some coding experience, who want to learn how to apply deep learning and machine learning to practical problems.
#deeplearning
Join 👉🏻@coursenuggets for more
Our other channels @datasciencechats @kdnuggets
https://course.fast.ai/

Join our LinkedIn group to access. Open for all for limited period.
#datascience #path
@kdnuggets @datasciencechats
https://www.linkedin.com/groups/13661437

1 hour mini course for Chatgpt with Python
Exclusively Free for limited period
@kdnuggets @datasciencechats
https://www.udemy.com/course/chatgpt-api-python-masterclass-with-google-apps-integration/?couponCode=NEWDAY

https://www.classcentral.com/report/openai-chatgpt-course/
#chatgpt
For more @coursenuggets

Microsoft announcements #generativeai
@kdnuggets @datasciencechats
https://www.instagram.com/reel/Cu4AbqAM444/?igshid=Y2I2MzMwZWM3ZA==

MediSearch gives direct answers to medical questions based on trust worthy sources using llms
https://medisearch.io
#llm #machinelearning
@kdnuggets @datasciencechats

Language translation + speech recognition + speech synthesis in a single model: speech-to-speech, text-to-text, speech-to-text and text-to-speech.

Works for 100 languages.
Code available under CC-BY-NC license.
From Meta - Fundamental AI Research.
#meta #speech #language #text

Blog post: https://bit.ly/45z0e6s
Details ➡️ https://bit.ly/47In6m0
Demo ➡️ https://bit.ly/45jjYLz
Code ➡️ https://bit.ly/3KRne8W

@kdnuggets @datasciencechats

Stanford online has released the course videos on "Natural Language Understanding" by Professor Christopher Potts.

The course covers topics including
⦿ Intro & evolution of NLU
⦿ Contextual word representations
⦿ Information retrieval
⦿ In-context learning
⦿ Behavioural evolution of NLU models
⦿ Analysis methods for NLU
⦿ NLP methods and metrics
⦿ Presenting your research
⦿ Language models and how to build them

@datasciencechats @kdnuggets
#stanford #nlp
Credit: Linkedin Sudalai Rajkumar

https://www.youtube.com/playlist?list=PLoROMvodv4rOwvldxftJTmoR3kRcWkJBp

Virtual Medicine has created the most advanced, multi-award winning medical anatomy platform crossing Virtual Reality (VR), Mixed Reality (MR), and Augmented Reality (AR) for medical education.
@kdnuggets @datasciencechats
#VR #AR

https://www.instagram.com/reel/CwUbqbZqTuI/?igshid=MzRlODBiNWFlZA==

Join our instagram channel for more:
https://www.instagram.com/kdnuggets/

Python in Excel – making it possible to integrate Python and Excel analytics within the same Excel grid for uninterrupted workflow.
@kdnuggets @datasciencechats
#python #excel
Blog:
https://techcommunity.microsoft.com/t5/microsoft-365-blog/introducing-python-in-excel-the-best-of-both-worlds-for-data/ba-p/3905482
Video:
https://www.youtube.com/watch?v=H4XbvL8Mglc

https://blog.google/technology/ai/google-gemini-ai/amp/
#artificialintelligence #gemini
@kdnuggets @datasciencechats