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Krish Naik Hindi
Индия
Добавлен 4 дек 2017
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#1-New Series Building Generative AI App With HuggingFace Open Source Models With Langchain
Hugging Face x LangChain : A new partner package in LangChain
langchain_huggingface, a partner package in LangChain jointly maintained by Hugging Face and LangChain. This new Python package is designed to bring the power of the latest development of Hugging Face into LangChain and keep it up to date.langchain-huggingface integrates seamlessly with LangChain, providing an efficient and effective way to utilize Hugging Face models within the LangChain ecosystem. This partnership is not just about sharing technology but also about a joint commitment to maintain and continually improve this integration.
Code: github.com/krishnaik06/Gen-AI-With-Hugging-Face
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langchain_huggingface, a partner package in LangChain jointly maintained by Hugging Face and LangChain. This new Python package is designed to bring the power of the latest development of Hugging Face into LangChain and keep it up to date.langchain-huggingface integrates seamlessly with LangChain, providing an efficient and effective way to utilize Hugging Face models within the LangChain ecosystem. This partnership is not just about sharing technology but also about a joint commitment to maintain and continually improve this integration.
Code: github.com/krishnaik06/Gen-AI-With-Hugging-Face
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Просмотров: 2 114
Видео
Turn Your Computer Into Gen AI Computer- Krish Naik Hindi
Просмотров 1,4 тыс.Месяц назад
Some of the amazing features of Jan ai Run AI models like Llama or Mistral directly on your device for enhanced privacy. No need for an internet connection- keep all your data and processing locally. Connect to remote APIs, like OpenAI, Groq, or Mistral API. Access AI capabilities without needing advanced hardware, with all processing handled in the cloud. Conversations, preferences, and model ...
Run Pandas Library 50x Time Faster on Google Colab Using Rapids cuDF - Krish Naik Hindi
Просмотров 917Месяц назад
At Google I/O’24, Laurence Moroney, head of AI Advocacy at Google, announced that RAPIDS cuDF is now integrated into Google Colab. Developers can now instantly accelerate pandas code up to 50x on Google Colab GPU instances, and continue using pandas as data grows-without sacrificing performance. RAPIDS cuDF is a GPU DataFrame library that accelerates the data processing tool pandas with zero co...
Project Astra Future of AI Assistants-Will It Beat GPT-4o(onmi)
Просмотров 538Месяц назад
Introducing Project Astra. We created a demo in which a tester interacts with a prototype of AI agents supported by our multimodal foundation model, Gemini. There are two continuous takes: one with the prototype running on a Google Pixel phone and another on a prototype glasses device. The agent takes in a constant stream of audio and video input. It can reason about its environment in real tim...
Getting started With Google's PaliGemma: Open Vision-Language Model
Просмотров 628Месяц назад
PaliGemma is a powerful open VLM inspired by PaLI-3. Built on open components including the SigLIP vision model and the Gemma language model, PaliGemma is designed for class-leading fine-tune performance on a wide range of vision-language tasks. This includes image and short video captioning, visual question answering, understanding text in images, object detection, and object segmentation. Cod...
Getting Started With Google Gemini Flash MultiModal With Implementation
Просмотров 1,3 тыс.Месяц назад
Flash has a one-million-token context window by default, which means you can process one hour of video, 11 hours of audio, codebases with more than 30,000 lines of code, or over 700,000 words. Google Gemini Flash: deepmind.google/technologies/gemini/flash/ Code :colab.research.google.com/github/google/generative-ai-docs/blob/main/site/en/tutorials/quickstart_colab.ipynb#scrollTo=j51mcrLD4Y2W Pl...
Google IO 2024 Recap In 5 min-Gemini Pro Vs OpenAI GPT-4o(omni)
Просмотров 891Месяц назад
Google IO 2024 Recap In 5 min-Gemini Pro Vs OpenAI GPT-4o(omni)
Demo Of OpenAI GPT-4o(Omni) In Mobile App With Audio Conversation
Просмотров 2 тыс.Месяц назад
GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction-it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time(opens in a new window) in a conver...
Open AI New GPT-4o Model Beats All GPT Models-Live Demo
Просмотров 8 тыс.Месяц назад
GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction-it accepts as input any combination of text, audio, and image and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time(opens in a new window) in a conversation....
How Do I Stay Updated In The AI Field- Krish Naik Hindi
Просмотров 1,1 тыс.Месяц назад
In this video we will be talking how I keep mysself updated in the field of AI Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more ruclips.net/channel/UCNU_lfiiWBdtULKOw6X0Digjoin All Playlist links are given below Langchain Playlist: ruclips.net/video/tEL833CPhqw/видео.html NLP Playlist: ruclips.net/p/PLTDARY...
Analyzing Generative AI Engineers Job Market- Krish Naik Hindi
Просмотров 693Месяц назад
In this video we will be analysing the job market of Generative AI Engineers and what skillset we require to crack this market. Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more ruclips.net/channel/UCNU_lfiiWBdtULKOw6X0Digjoin All Playlist links are given below Langchain Playlist: ruclips.net/video/tEL833CPh...
Tutorial 5-Building Advanced RAG With Multiple Data Source Using Langchain-Krish Naik Hindi
Просмотров 1,2 тыс.Месяц назад
Hello All we are going to build Advanced RAG Projects With Multiple Data Sources as arxiv,wikipedia and others .Here we will be learnign about agents,tools,toolkits and agent executor github: github.com/krishnaik06/Updated-Langchain/tree/main/agents Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more ruclips.n...
Complete Generative AI Projects Lifecycle- Krish Naik Hindi
Просмотров 1,4 тыс.Месяц назад
In this video we will discuss about the complete Generative AI Projects Lifecycle including cloud platforms like AWS, Azure and GCP Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more ruclips.net/channel/UCNU_lfiiWBdtULKOw6X0Digjoin All Playlist links are given below Langchain Playlist: ruclips.net/video/tEL83...
Tutorial 4-Advanced RAG Q&A Chatbot With Chain And Retrievers Using Langchain- Krish Naik Hindi
Просмотров 1,1 тыс.2 месяца назад
In this video we will be creating an advanced Q&A chatbot using chains and retrievers from langchain. #langchain code github: github.com/krishnaik06/Updated-Langchain/tree/main/chain Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more ruclips.net/channel/UCNU_lfiiWBdtULKOw6X0Digjoin All Playlist links are give...
Tutorial 12-Word2vec CBOW And Skipgram Indepth Intuition NLP- Krish Naik hindi
Просмотров 1,2 тыс.2 месяца назад
CBOW and skip-gram are models of the Word2vec framework used in natural language processing. Word2Vec is a neural network model for word embeddings. Before diving into explaining what are embeddings, I have a question for you. How do we make machines understand text? The core idea behind word embeddings is to convert text to numerical data (vector space) and capture the semantic as well as synt...
Tutorial 3- Getting Started With Q&A RAG Pipeline Using Langchain- Krish Naik Hindi
Просмотров 1,3 тыс.2 месяца назад
Tutorial 3- Getting Started With Q&A RAG Pipeline Using Langchain- Krish Naik Hindi
Tutorial 11-Word2vec Word Embedding Indepth Intuition NLP- Krish Naik Hindi
Просмотров 1 тыс.2 месяца назад
Tutorial 11-Word2vec Word Embedding Indepth Intuition NLP- Krish Naik Hindi
Tutorial 2- Deployment Open Source And OpenAI LLM Project As API With Langchain Langserve & FastAPI
Просмотров 1,2 тыс.2 месяца назад
Tutorial 2- Deployment Open Source And OpenAI LLM Project As API With Langchain Langserve & FastAPI
Tutorial 10-Introduction To Word Embeddings- Krish Naik Hindi
Просмотров 7842 месяца назад
Tutorial 10-Introduction To Word Embeddings- Krish Naik Hindi
Tutorial 1- End To End Q&A Chatbot Using OpenAI And Open Source LLM's using Langchain And Ollama
Просмотров 2,6 тыс.2 месяца назад
Tutorial 1- End To End Q&A Chatbot Using OpenAI And Open Source LLM's using Langchain And Ollama
Tutorial 9-TF-IDF Word Embedding Indepth Intuition- Krish Naik Hindi
Просмотров 8762 месяца назад
Tutorial 9-TF-IDF Word Embedding Indepth Intuition- Krish Naik Hindi
Tutorial 8- Ngrams Indepth Intuition In NLP- Krish Naik Hindi
Просмотров 8372 месяца назад
Tutorial 8- Ngrams Indepth Intuition In NLP- Krish Naik Hindi
Tutorial 7-Bag Of Words Text Embedding Indepth Intuition In NLP- Krish Naik Hindi
Просмотров 7762 месяца назад
Tutorial 7-Bag Of Words Text Embedding Indepth Intuition In NLP- Krish Naik Hindi
Tutorial 6-One Hot Encoding Word Embedding Indepth Intution In NLP- Krish Naik Hindi
Просмотров 9252 месяца назад
Tutorial 6-One Hot Encoding Word Embedding Indepth Intution In NLP- Krish Naik Hindi
Tutorial 5- Plan Of Learning Text Embedding In NLP- Krish Naik Hindi
Просмотров 1 тыс.2 месяца назад
Tutorial 5- Plan Of Learning Text Embedding In NLP- Krish Naik Hindi
Roadmap To Become AI Engineer In 2024- Krish Naik Hindi
Просмотров 7 тыс.2 месяца назад
Roadmap To Become AI Engineer In 2024- Krish Naik Hindi
AI Engineers Vs ML Engineers Vs Data Scientist- Krish Naik Hindi
Просмотров 4,2 тыс.2 месяца назад
AI Engineers Vs ML Engineers Vs Data Scientist- Krish Naik Hindi
How To Prepare For Job Market 2024- Krish Naik Hindi
Просмотров 4,4 тыс.2 месяца назад
How To Prepare For Job Market 2024- Krish Naik Hindi
Github materials for Learning Data science And Gen AI For Free- Krish Naik Hindi
Просмотров 7 тыс.3 месяца назад
Github materials for Learning Data science And Gen AI For Free- Krish Naik Hindi
Langchain New Series- Why Langchain And Understanding Langchain Ecosystem- Krish Naik Hindi
Просмотров 3,7 тыс.3 месяца назад
Langchain New Series- Why Langchain And Understanding Langchain Ecosystem- Krish Naik Hindi
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Sir full stats ki class upload kr jiye
great explanation sir..
👌
sir stats series continue wen?
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Please upload the class on box cox transformation
Thank you ...Sir🙏
Can I get this notepad pdf???
Sir I am bnys student but mujhe generative AI main interest hai main kaise enter kar sakti hu??
Thank you sir
nice explanationn
in RSME GRAPH is differentiable, has same unit, mostly used in deep learning. disadvantage - not robust to outliers
Nice explanation bro thank you❤
sir you said some Types Of Cross Validation not work with imbalanced dataset,, so how we check that the dataset is imbalanced???
love you
👌
everything explained in very easy way ...please make video of math's of 11 12 class because we are not getting a right channel to clear the math's doubt, we didn't know which major topic we should have to cover in math's...we are just lacking in log, differentiation, linear algebra, calculus...i just request to please cover major topic of math's
maths ki bhi ek playlist bnao app toh
you talk about the research paper that you will discuss. Do share the link of paper also
well the simplicity of teaching method is commendable!!🤌🤌🤌
Print(arr1[0:,::3])
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Thank you very much sir.
Sir, 10:00 SETS are unordered collections, In your first example, print({3, 1, 2, 3, 4}) outputs {1, 2, 3, 4} because the hash values of the integers are used to determine the iteration order, it happens to be in ascending order. In your second example, print({"IronMan", "Avengers", 'Hitman'}) outputs {'Avengers', 'Hitman', 'IronMan'} because the hash values of the strings are used to determine the iteration order, it happens to be in a particular order that looks like it's sorted alphabetically. However, this is not guaranteed and can change depending on the Python implementation or version.
which book is best for statistics in machine learning
Where can I get the jupyter notebook , the GitHub repo only contains the pdf notes of theory lecture Plz tell if anyone knows
Age 16 Whose See this lecture
Where can I find the material? Please provide me with the link
too complex🙁
16:38
Link not working sir
k means for large dataset and hierarchial for small dataset
Thanks for guidance and motivation. May Allah bless you and yiur family!!! Dil se dua
8:53 why "n+1" why not "n"
Why n+1 , only n why not
exam me google nhi khulta hai chacha
sir please explain more
8:05 percentile value of 11 is 95 percentile
print(arr[:,0::4])
3:55 Start
i truly appreciate your hardwork.. its just so easy to adapt. You are such a gem as a teacher sir.
Thank you sir🤗
Sir make a video on ai chatbot
Great thank you
Good explanation
There is no large image model but it is known big data.
It is a large language model but not a large image model as you said.
its amazing
Paired and unpaired ka concept????