Suleman Muhammad

Skilledscore empowers individuals to take charge of their professional futures. Whether you're starting, stuck, or seeking to accelerate your career, we have the tools and guidance you need.

Visa Bridge, the most innovative AI-driven Immigration Consultant platform, simplifies the complexities of immigration and the visa process, making it easier than ever before. With global adaptability on the rise, choosing the best country to migrate to is becoming increasingly challenging. Visa Bridge revolutionizes this process by analyzing your CV and recommending the best countries out of 200 options worldwide.


Simply upload your CV, and its advanced AI software will handle the… Show more

Visa Bridge, the most innovative AI-driven Immigration Consultant platform, simplifies the complexities of immigration and the visa process, making it easier than ever before. With global adaptability on the rise, choosing the best country to migrate to is becoming increasingly challenging. Visa Bridge revolutionizes this process by analyzing your CV and recommending the best countries out of 200 options worldwide.


Simply upload your CV, and its advanced AI software will handle the rest. It offers personalized recommendations, providing detailed information on finding a job, getting a driver’s license, buying a home, and everything else you need to know about your top three chosen countries. This is achieved through extensive data analysis on social media platforms such as Reddit, Twitter, and Facebook, gathering real-life experiences from students, skilled professionals, entrepreneurs, medical doctors, pharmacists, and other experts. Show less

Description for the 191 youtube channels , youtube channel videos. include title, description, view_count, publish_date, length, author. This CSV dataset contains detailed information about videos YouTube channel, last update on June 24, 2024.

Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks are powerful tools for sequential data tasks, such as natural language processing. This project demonstrates how to use these models to predict the next word in a sentence, leveraging the ability of RNNs and LSTMs to maintain context over sequences.

Image categorization using tensorflow, deep learning neural model training

Excited to share that I've developed an AI chatbot for the BBC YouTube channel! We've processed transcripts from 4,588 videos, covering content from September 2022 to June 18, 2024. You can try it out here: https://bbcaichatbot.streamlit.app/. Please note that it's currently deployed on free hosting, so you might encounter some loading glitches. Feedback is welcome!

This project allows you to upload multiple PDF files and interact with them using natural language questions and answers. It leverages NVIDIAEmbeddings, ChatNVIDIA, OllamaEmbeddings, and FAISS to provide efficient and accurate responses.

This CSV dataset contains detailed information about videos from Zeeshan Usmani's YouTube channel, spanning from October 5, 2022, to June 21, 2024. The dataset includes the following columns:

Id: A unique identifier for each video.
Title: The title of the video.
View_count: The number of views the video has received.
Thumbnail_url: The URL of the video's thumbnail image.
Publish_date: The date when the video was published.
Length: The duration of the video.
Author: The… Show more

This CSV dataset contains detailed information about videos from Zeeshan Usmani's YouTube channel, spanning from October 5, 2022, to June 21, 2024. The dataset includes the following columns:

Id: A unique identifier for each video.
Title: The title of the video.
View_count: The number of views the video has received.
Thumbnail_url: The URL of the video's thumbnail image.
Publish_date: The date when the video was published.
Length: The duration of the video.
Author: The author of the video.
This dataset was utilized in developing the Zeeshan Usmani AI Chatbot, which you can access here.
https://zusmanichatbot.streamlit.app/
For complete transcripts in English or any other language, please send an email request. Show less

This project aims to provide a streamlined process for fine-tuning models with custom data using Google Cloud Platform (GCP) services, particularly leveraging Vertex AI. Fine-tuning models is crucial for various machine learning tasks, such as improving the performance of pre-trained models on specific domains or tasks.

## Features

- **Efficient Fine-tuning**: Utilize the power of Google Cloud Platform for efficient fine-tuning of machine learning models.
- **Custom Dataset… Show more

This project aims to provide a streamlined process for fine-tuning models with custom data using Google Cloud Platform (GCP) services, particularly leveraging Vertex AI. Fine-tuning models is crucial for various machine learning tasks, such as improving the performance of pre-trained models on specific domains or tasks.

## Features

- **Efficient Fine-tuning**: Utilize the power of Google Cloud Platform for efficient fine-tuning of machine learning models.
- **Custom Dataset Support**: Easily integrate your custom dataset for fine-tuning tasks.
- **Scalability**: Scale your fine-tuning process seamlessly with GCP's infrastructure.
- **Vertex AI Integration**: Harness the capabilities of Vertex AI for model training and deployment.
- **Monitoring and Logging**: Monitor and log fine-tuning experiments for better tracking and analysis.
- **Cost-effectiveness**: Optimize costs with efficient resource utilization on Google Cloud. Show less

This repository contains a chat application that allows users to upload multiple files, processes these files to extract information, and then uses an AI model (OpenAI's GPT-4) to answer questions or provide insights based on the content of the files. The application is built using Streamlit for the front-end interface, LlamaIndex for indexing and searching through the content, and OpenAI for the natural language processing capabilities.

Website-to-MCQs is an application built in Python that utilizes generative AI, Langchain, embedding techniques, and ChatGPT to automatically generate multiple-choice questions (MCQs) from website content.

This repository contains the source code for the Google Generative AI Gemini App, designed to retrieve data directly from a SQL Server database. The application leverages Google Generative AI to provide intelligent querying and data retrieval capabilities.

QuestionAnswer application using ObjectBox vector database, Gpt4o and langchain

RAG QuestionAnswer Application with ObjectBox, GPT-4, and LangChain

Image Generations API
The Image Generations API allows you to create original images based on text prompts. It utilizes the DALL·E model, which can generate images of varying sizes.

This project aims to develop an end-to-end chat bot system that interacts with a local SQL database CSV file. The system utilizes Streamlit for creating interactive web applications, LangChain for natural language processing (NLP), and ChromeDB for managing the SQL database. The entire system is implemented in Python.

This project aims to create a Question and Answer (QA) similarity search application using Python. It leverages various libraries and tools including Jupyter Notebook, Pinecone, Vector Database, LangChain, RetrievalQA, ChatGPT, OpenAIEmbeddings, PineconeVectorStore, PyPDFDirectoryLoader, and RecursiveCharacterTextSplitter.

Welcome to RAG Chat, your local Retrieval Augmented Generation (RAG) pipeline! This application allows you to interactively chat with your PDF files using the power of Ollama and LangChain.

Features
RAG Pipeline: Utilizes the latest advancements in NLP with Llama3 and Ollama to process and enhance your PDF documents.
Interactive Chat: Engage in conversational interactions with your PDF content, asking questions and getting detailed responses.
LangChain Integration: Seamlessly… Show more

Welcome to RAG Chat, your local Retrieval Augmented Generation (RAG) pipeline! This application allows you to interactively chat with your PDF files using the power of Ollama and LangChain.

Features
RAG Pipeline: Utilizes the latest advancements in NLP with Llama3 and Ollama to process and enhance your PDF documents.
Interactive Chat: Engage in conversational interactions with your PDF content, asking questions and getting detailed responses.
LangChain Integration: Seamlessly integrates with LangChain for enhanced language understanding and generation.
Local Processing: All processing is done locally, ensuring data privacy and security. Show less

This project is dedicated to creating a robust Question and Answer (Q&A) similarity search application using Python including Jupyter Notebook, Chroma Database, Vector Database, LangChain, large language models, RetrievalQA, ChatGPT, OpenAI Embeddings, PyPDFDirectoryLoader, and RecursiveCharacterTextSplitter

This project aims to automate the process of generating multiple-choice questions (MCQs) using Generative AI techniques. Users can upload a text file containing relevant content, and our system utilizes Streamlit for the frontend, Python for backend processing, LangChain, LLM (Large Language Models), ChatGPT, and SequentialChain for generating MCQs. The entire system is deployed on AWS EC2 using MLOps methodologies for seamless integration and deployment.

Features
File Upload: Users… Show more

This project aims to automate the process of generating multiple-choice questions (MCQs) using Generative AI techniques. Users can upload a text file containing relevant content, and our system utilizes Streamlit for the frontend, Python for backend processing, LangChain, LLM (Large Language Models), ChatGPT, and SequentialChain for generating MCQs. The entire system is deployed on AWS EC2 using MLOps methodologies for seamless integration and deployment.

Features
File Upload: Users can upload text files containing the content for which MCQs need to be generated.
Generative AI: Leveraging advanced AI models including LangChain, LLM, ChatGPT, and SequentialChain for MCQ generation.
Streamlit Interface: A user-friendly frontend powered by Streamlit for easy interaction.
AWS EC2 Deployment: The system is deployed on AWS EC2 for scalability and reliability.
MLOps Integration: Utilizing MLOps practices for continuous integration and deployment. Show less

Unlock the power of LangChain & ChatGPT: Load your data (text, PDF, etc.), query with prompts, gain insights! Get started now.

Explore the power of LangChain and ChatGPT with our comprehensive guide on loading custom data and utilizing prompts for insightful inquiries. Whether your data is in text file, PDF, or any other format, this repository provides step-by-step instructions and code snippets to seamlessly integrate LangChain and ChatGPT into your workflow. Empower your data… Show more

Unlock the power of LangChain & ChatGPT: Load your data (text, PDF, etc.), query with prompts, gain insights! Get started now.

Explore the power of LangChain and ChatGPT with our comprehensive guide on loading custom data and utilizing prompts for insightful inquiries. Whether your data is in text file, PDF, or any other format, this repository provides step-by-step instructions and code snippets to seamlessly integrate LangChain and ChatGPT into your workflow. Empower your data exploration journey and unlock meaningful insights through natural language queries. Dive in today and revolutionize your data analysis experience! Show less

Excited to share my latest GitHub project where I delve into the world of advanced Natural Language Processing (NLP) and Machine Learning (ML) to craft personalized ChatGPT models. Leveraging cutting-edge techniques, I focus on generating high-quality vector representations of textual data for diverse applications such as search and sentiment analysis.

Key Features:

Data Collection and Preprocessing: Gather and preprocess relevant text data ensuring consistency and cleanliness… Show more

Excited to share my latest GitHub project where I delve into the world of advanced Natural Language Processing (NLP) and Machine Learning (ML) to craft personalized ChatGPT models. Leveraging cutting-edge techniques, I focus on generating high-quality vector representations of textual data for diverse applications such as search and sentiment analysis.

Key Features:

Data Collection and Preprocessing: Gather and preprocess relevant text data ensuring consistency and cleanliness through tasks like tokenization and stopword removal.
LangChain Integration: Harness LangChain's capabilities for advanced text analytics including sentiment analysis and entity recognition to extract meaningful insights.
Model Training and Customization: Fine-tune ChatGPT models using the OpenAI API, adapting them to specific domains through techniques like transfer learning.
Enhanced Functionality: Implement zero-shot and few-shot prompting, and connect ChatGPT to external resources for expanded functionality, chatgpt function calling (connect large language model to external resource)

Join me on GitHub to explore the intricacies of personalized ChatGPT models and revolutionize human-computer interactions through tailored AI solutions. Let's collaborate and innovate in the realm of NLP and ML! #NLP #ML #ChatGPT #GitHub #AIinnovation Show less

Successfully deployed a machine learning project employing linear regression through ZenML. Utilized a data-centric approach, emphasizing continuous enhancement of the data while maintaining a stable model, as opposed to a model-centric technique. Achieved optimal results through iterative improvements to the dataset. #MachineLearning #DataCentricApproach #ZenML #LinearRegression

Currently I have been doing a research on Block Chain and How we can reduce the countries import bill and trade deficit problem by using the crypt currency and Block Chain.

Company Innon, Innon sale different types of devices which measure the energy(Gas, Water, electricity) consumption and save the data into sql server database table, Each device has its own table. Innon has thousands of devices install into different location in UK. Each device send data (time span and value) after every fifteen sec.

Project Name Data Analytics Web base application and Data ware house.

Role Team Lead

Problem Million of raw data inserted every day into SQL… Show more

Company Innon, Innon sale different types of devices which measure the energy(Gas, Water, electricity) consumption and save the data into sql server database table, Each device has its own table. Innon has thousands of devices install into different location in UK. Each device send data (time span and value) after every fifteen sec.

Project Name Data Analytics Web base application and Data ware house.

Role Team Lead

Problem Million of raw data inserted every day into SQL server database. The web analytics application querying that raw data for present into different graph to measure the energy consumption.

the first problem is query to Sql database taking to long to get the rows from the SQL server Database. the sec problem is after getting the rows from SQL database need to implement business logic which also taking too long to perform business operation.

Solution

In order solve this problem I redesign the application, Build the complete solution on n-tier architecture, the legacy application build on two tier architecture. I divided complete solution into following tiers

Raw Database
Data ware house
Web Api
Front end analytical webapplication
First problem solution, now we have aggregated data into data ware house and query taking very less time to to get the data from data ware house.

Sec Problem I used entity framework and json for business operation which also less time consuming and no need to convert any data format for different charts on front level.

I learned from project this how to build data ware house and aggregation of data. Show less

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A suite of around eight applications for the ARY Media and Research department.

customized news gathering and rundown application for the ARY News. Automated with the professional CGs and teleprompters.