Google announced Gemini 2.0, a more advanced AI model capable of native image and audio output and tool use. This new model powers several projects, including Project Astra (a universal AI assistant) and Project Mariner (browser-based task completion). Gemini 2.0 Flash, an experimental version, is available to developers, with wider release planned. Google emphasizes responsible AI development, prioritizing safety and security in its applications. The announcement highlights Gemini 2.0's integration into Google products and its potential to revolutionize user experience
https://blog.google/technology/google-deepmind/google-gemini-ai-update-december-2024/
#gemini
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If you are a fresher important to realise how important data structures and algorithms are in your preparation to get into software journey. Here is a well documented roadmap that you could use with any programming language. If you are looking to expand into datascience then via python 🐍
#beginner #datastructure #python #fresher
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Curated list of Artificial Intelligence courses, books 📚,video lectures and papers 📝
https://github.com/owainlewis/awesome-artificial-intelligence
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#courses #ai
https://blog.google/technology/ai/google-gemini-ai/amp/
#artificialintelligence #gemini
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Python in Excel – making it possible to integrate Python and Excel analytics within the same Excel grid for uninterrupted workflow.
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#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
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
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#stanford #nlp
Credit: Linkedin Sudalai Rajkumar
https://www.youtube.com/playlist?list=PLoROMvodv4rOwvldxftJTmoR3kRcWkJBp
MediSearch gives direct answers to medical questions based on trust worthy sources using llms
https://medisearch.io
#llm #machinelearning
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https://www.classcentral.com/report/openai-chatgpt-course/
#chatgpt
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Differences between RAG, Agents and Agentic RAG
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Who all are participating here? If you havent there is still time to participate and get trained for free. Highly recommend if you want to learn genai in short span of time. Are you doing? Comment below.
Читать полностью…The AI for Impact Hackathon, presented by Google Cloud and powered by Hack2skill, is a unique opportunity to leverage the transformative power of AI to address pressing social challenges across the APAC region.
You can participate in the hackathon for free with below link.
Deadline: 17th Nov
Register : https://bit.ly/4hEcMQI
AI Python for beginners Free course for limited period by Andrew Ng
#ai #python
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https://www.deeplearning.ai/short-courses/ai-python-for-beginners/
Did you know we have a linkedin community where useful datascience related posts are shared frequently?
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Marketing strategy and AI-Free Webinar from Google
In this session you will learn:
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AI-powered marketing tools you can try
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https://bit.ly/googleaimarketing
#ai #freecourse #marketing
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500 AI Machine Learning Projects list with code
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#github #projects
https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
Sponsored Post
Yachay.ai (https://www.yachay.ai/) has launched a machine learning hackathon focused on advancing the development of text-to-location models. Participants have the chance to win a prize of $500! If you're up for the challenge, here are instructions to participate: https://github.com/Yachay-AI/confident-predictions-challenge. The submission deadline is November 25, 2023.
Yachay.ai team has built and open-sourced a architecture for geotagging models that take textual inputs and produce coordinates as outputs. Codebase here: https://github.com/Yachay-AI/byt5-geotagging. Currently, they are actively seeking ways to enhance validation metrics.
If you are looking for ideas on leveraging geotagging models in your projects, join the discussion on potential use cases: https://discord.com/invite/PaqpppYTxs
Yachay.ai plans to release a downloadable model for Spanish texts and provide more free text/coordinates datasets in the near future. Stay tuned for updates!
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.
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#VR #AR
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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
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Microsoft announcements #generativeai
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1 hour mini course for Chatgpt with Python
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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.
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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