I'm Mohamed Niang, machine learning scientist and deep learner. I like to build something with Neural Network's. I like to learn new things and based on it to write repositories. I'm a big fan of large languages modeling (LLMs) and human level vision AI technologies based on Transformers (Attention Network's). I am currently a machine learning engineer at IBM, working on Pure MLOps for Recommender System.
Here, a repository to learn the basics of programming with Python.
- I am passionate about developing and applying machine learning methods for building algorithms and predictive models using a variety of datasets for solving impactful real world problems. I learn continuously hard on projects regarding machine learning, deep learning and robotics. I am currently interested in the field of generative ai, cloud computing and data science.
Here, to find some of my publications on medium. These publications cover topics such as introduction to Tensorflow, object-oriented programming and other interesting topics on data science and artificial intelligence.
Here are the languages I use most often in my personal projects.
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- Computer-Vision-for-Autonomous-Cars
Computer-Vision-for-Autonomous-Cars PublicThis repository contains some explanations on how autonomous driving works with computer vision and some practical cases on the subject.
- Data-Science-With-Python
Data-Science-With-Python PublicThis repository contains an introduction to data science with Python.
Jupyter Notebook 3
- Human-Activity-Recognition
Human-Activity-Recognition PublicHuman Activity Recognition from Wearable Inertial Sensor Networks with Machine Learning.
- Object-Detection-using-YOLO
Object-Detection-using-YOLO PublicObject Detection using Yolo with OpenCV.
Jupyter Notebook 1
- APIs-Web-Scraping-in-Python
APIs-Web-Scraping-in-Python PublicThis repository contains notebooks on APIs and Web Scrapping in Python.
Jupyter Notebook
- Customers-Segmentation-Using-ML
Customers-Segmentation-Using-ML PublicThis repository contains notebooks based on kaggle challenge of customers segmentation using ML.
Jupyter Notebook
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