Senior Data Scientist

Jibe Solution

1. Ludex:
2. create a model for find the sport cards using VLID descripts and year classifier. in this project I create
3. training pipeline using sagemaker-sdk on aws. sport Finding model deploy on ec2 server. user request
4. handling using RebitMQ. And search on large data using milivus.
5. website link, https:// www.ludex.com
6. Libraries:
7. TensorFlow, pytorch, milieus, RabbitMQ, Aws, Ec2-server, S3, lambda function, sagemaker notebook AWS,
8. MLOps, VS-code
9. Prediction Next ports:
10. using the previous traveling history of the vessel predict the next 5 Ports and also to similarities. deploy
11. model using ML-studio Azure and Databricks to create pipeline.
12. Libraries:
13. TensorFlow, data bricks on azure, ML-studio Azure, Azure-Devops , Sk-learn, Pycharm, Azure Databricks
14. NER for Certificate:
15. using the name entity recognizer model extract the issue date, expire date, name and company name from
16. pdf certificate. Model training on Azure Databricks
17. Libraries:
18. Azure-ml_studio, Azure-Databricks, Azure-devops , SK-learn, pycharm
19. Table detection:
20. using cascadetabnet detect table borderless or not on pdf deploy on Azure ml-sudio using registry the
21. model.
22. libraries:
23. ML-studio-gpu, azure-databricks VS-code
24. Product DBM:
25. using the OCR to extract the Text data from pdf than apply some NLP technique to find component main,
26. main machinery and other parts of the vessel. using Databrick to analysis data from MangoDB
27. website link, https://dbm.jibe.solutions
28. libraries:
29. EC2 server GPU, S3, lambda, azure-databricks VS-code
30. Jibe eye:
31. ABOUT ME
32. WORK EXPERIENCE
33. this product deploy inside the ship. This product contain multiple computer vision model like help
34. detection, face detection, violence detection. and main part detection in side the ship on real time. create
35. docker to help on deploy side and health check for the system
36. libraries:
37. system GPU, docker, bash script, VS-code, tensorflow

Senior data scientist

GCS Pvt

1. Deploy model on Azure
2. • Create Recommend system for E-commerce on Azure ML-studio, and deploy using ML-studio and
3. Databricks
4. • create a market analysis using SQL
5. • working on the Lambda function
6. Pakistan Railway Face recognition base Attendance :
7. create a face recognition system in Pakistan Railway using Machine learning. in this project working
8. in Realtime environment. this project was very challenging for us, because of light and resource
9. effects. In this project, we get 99% accuracy against 3000 employees in one site
10. Libraries:
11. TensorFlow, MySQL, panda, NumPy, OpenCV, keras, Azure-mlstudio, K-near neighbor, Sklearn,
12. Pycharm
13. Pakistan Railway Train Tracking system:
14. in this project working to track train using tagging system. read tag using tag reader device and
15. update with time, speed. and location of the train.
16. Libraries:
17. SQL, panda, NumPy, Pycharm
18. NRTC Number Plates:
19. In this project working on NRTC to create number of Plates. using peddle OCR for reading laser
20. number and yolov4 for (laser number detection ) object detection. In this project working on
21. raspberry pi and deploy model on raspberry pi

AI engineer

No Border Innovation

1. News recommender system:
2. Create news recommendations system using deep learning. In this project I create model
3. structure using tensorflow. This recommendation working on content-based filtering.
4. Libraries: tensorflow, pandas, sql, numpy, keras
5. ❖ Instagram chat bot
6. Create bot for Instagram who help upload your picture on your profile. And like,
7. comments and followings other users on Instagram.
8. Libraries: tensorflow, pandas, sql, numpy, NLtk
9. ❖ General Chat-bot:
10. Create a chat bot who communicates with other people and find the interest of that
11. person. This bot store personal information of the user who use it.
12. Libraries: tensorflow, sql, pytroch, panda, numpy
13. ❖ Working to creating text to summarization
14. ❖ create AI model to predict the cryptocurrencies after five mins prices
15. ❖ create 2-D image to 3-D mesh

AI engineer

Innovate Solutions

1. Used LSTM and GRU create a model to predictive next 7, 15- and 30 minute price of the stock. Create
2. model to detect news fake or real using NLP and using transfer learning in Grover model. Worked in
3. Reinforcement learning to develop a model to beat Alpha-Zero model in chess or other games. Worked in
4. text to voice using AI model in this model (dc-tts model ).
5. AI Chess:
6. In this project work in reinforcement learning. Using reinforcement learning create an algorithm for playing
7. a chess game more than super-man. In this project we beat the Alpha-zero and Leela chess in world
8. competition of AI chess.
9. Tools & libraries Used: python, DQN, CNN, Tesnsor-flow
10. Stock Predication:
11. The Goal of this project is to provide help and support to company customer to predict the price of the
12. stock and invest in stock markets. Objective to detect the prices of the stock price next 7,15 and 30 mins.
13. Our solution takes input as close price of stock different periods as different prediction days and giving the
14. price of the next days in stock
15. Tools Used: Python, RNN, FLASK,, PyTorch
16. News Revealer:
17. The Goal of this project is to provide a website in which detect the news is real or fake using the AI model.
18. In this project use the neutral network for train and predict response of different user about our project.
19. Tool Used: python, sql, Grover, Flask, NLP, and Tensorflow

university of gujrat

BS software engineering