Discover @ArslanKAS Open Source projects

Arsalan Ali (@ArslanKAS)

ArslanKAS

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Registered over 5 years ago
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Location 🇵🇰 Pakistan
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Prompt-Engineering-by-OpenAI

In ChatGPT Prompt Engineering for Developers, you will learn how to use a large language model (LLM) to quickly build new and powerful applications.

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LangChain-for-LLM-App-Development

The framework to take LLMs out of the box. Learn to use LangChain to call LLMs into new environments, and use memories, chains, and agents to take on new and complex tasks.

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Functions-Tools-and-Agents-with-LangChain

Explore new advancements like ChatGPT’s function calling capability, and build a conversational agent using a new syntax called LangChain Expression Language (LCEL) for tasks like tagging, extraction, tool selection, and routing.

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Large-Language-Models-with-Semantic-Search

Explore from keyword search to dense retrieval and reranking, which injects the intelligence of LLMs into your search system, making it faster and more effective.

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Building-Machine-Learning-Demos-with-Gradio

In this course you'll learn to use Gradio to create user-friendly apps with minimal code: Summarize text using a large language model, generate image captions, and chat with an open source LLM. Gain practical knowledge to build interactive demos faster.

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Quality-and-Safety-for-LLM-Applications

Explore new metrics and best practices to monitor your LLM systems and ensure safety and quality

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Python-Chilla-2.0

All the content that I learned through two Courses. One is called "Python Chilla" and the second one is called "100 Days of Machine Learning"

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Projects

HuggingFace

HugginFace for Beginners

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ChatGPT-Python

OpenAI Model integration with Python through OpenAI API

ML_pipeline

Machine Learning Project Pipeline

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ArslanKAS

Config files for my GitHub profile.

Sastaticket-Flight-Competition

SastaTicket Flight Forecasting

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Pair-Programming-with-LLM

Learn how LLMs can enhance, debug, and document your code in this new course built in collaboration with Google

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Serverless-LLM-Amazon-Bedrock

You’ll learn how to deploy a large language model-based application into production using serverless technology

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Selenium

This is basic Selenium crash course where I've tried out several automation concepts from testing out websites through actions, captcha, scraping etc

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Getting-Started-with-Mistral

Learn about selecting the right Mistral model for your use case, and get hands-on with features like effective prompting techniques, function calling, JSON mode, and Retrieval Augmented Generation (RAG).

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Quantization-Fundamentals

Learn to compressing models through methods such as quantization to make them more efficient, faster, and accessible

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MLfromscratch

Machine Learning algorithm implementations from scratch.

Oil---Gas

Data Analytics on the Insights of Upstream and Downstream of Oil Production for Forecasting

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Sentiment-Analysis

Sentiment Analysis of IMDb reviews

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Fake-News-Detection

Fake News Detection Model

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LangChain-Chat-with-your-Data

Using LangChain learn data loading, splitting, embeddings, and advanced retrieval techniques using over 80 unique loaders. Build question-answering solutions and chatbots with LangChain and LLMs for interactive data interaction.

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Git---GitHub

Git Cheatsheet for Beginners

FastAPI

Create APIs in Python using FastAPI

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GCP

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MYaseen208

Docker

Codewars

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