Muhammad Fawi's Projects
Doing Market Basket Analysis using Apriori Algorithm to recommend items that are frequently bought together to do up-sale using R and deploying the model in a Shiny App.
Clustering the manifold of the embeddings learned by autoencoders in python
Here in this tutorial, I am trying to address the limitation of many DL models in inferring unseen classes leveraging bayesian neural networks and how they exhibit certainty and uncertainty upon inference.
Binary search trees implementation in C
building a movie recommendantion enine leveraging a blend of graph-based machine learning and deep reinforcement learning (DRL).
Importing C libraries into Python using ctypes library
Using C priority queue library to execute process and scripts in different languages
Calling C Posix threads from python through cython
Predict user subscription using Logistic Regression, Decision Tree and Random Forest classifiers in Julia ...
Using Logistic regression to perform Machine Learning Classification task to predict whether a patient is diabetic or not based on certain analysis values.
Exploring Hierarchical and Kmeans Clustering algorithms in R trying to segment wholesale customers ...
developing a machine learning model with R and creating an API for it to enable it to connect with other applications and languages such as python and command line.
The code repository for the CURLoRA research paper. Stable LLM continual fine-tuning and catastrophic forgetting mitigation.
Compressing data using Python and compression techniques for better data storage and transfer.
Importing data from a web API in parallel , cleaning it and transforming it with the command line tools.
deep dive into how LoRA works under the hood, looking at its mathematical foundations by walking through a practical example
Building keras deep artificial neural networks to build a classifier able to predict forest cover type ...
Using R to draw some maps
Using SHapley Additive exPlainations (SHAP) library to explain a python machine learning model
Using R to demonstrate some feature engineering and selection techniques
Building a sentiment classifier on top of BERT's contextualized embeddings
Using various R packages and techniques to explore, analyze and sample big data files without reading the whole files.
Implementing hash table that uses separate chaining to avoid collisions. While in each indiex it uses binary search tree to achieve faster lookup.
Implementing separate chaining hash table data structure in C
Concurrency and interprocess communication through named pipes and shared memory along with parallelism through posix threads to get weather data from an API
Exploring Julia programming language in doing Data Science and Machine Learning .
Creating an sbt Apache Spark application to perform customer segmentation using Spark MLlib KMeans ...
Processing large data files using different R data.table package and Command Line tools.
My first steps in learning C
Implementing Levenshtein distance in C and Python