Syed Muhammad Hamza's repositories
Hybrid-recommendation-system-web-application
Regression-based Movie Recommender system that's a hybrid of content-based and collaborative filtering Recommender system Simply rate some movies and get immediate recommendations tailored for you
Myers-Briggs-Type-Indicator-MBTI-classification-Web-App
Myers–Briggs Type Indicator (MBTI) classification where my classifier can classify your personality type based on Isabel Briggs Myers self-study Myers–Briggs Type Indicator (MBTI). The classification result can be further used to match people with the most compatible personality types
AndroidCipherApplication
An Android-based application build using the MVC model That allows users to Encipher(encrypt) and Decipher( decrypt) text using using following Ciphers - Shift Cipher - Vigenere Cipher - Substitution Cipher - Playfair Cipher
Consumer-Finance-Complaints-Text-classification-with-PostgreSQL
Classifying Consumer Finance Complaints into one of eleven product categories, The problem is a Text classification, also known as text tagging or text categorization. Text classifiers can automatically analyze text and then assign a set of pre-defined tags or categories based on its content. In this problem, I have taken 'consumer_complaint_narrative' as “text” and to classify each consumer_complaint_narrative / “text” into one of eleven pre-defined categories of product.
Machine-Learning-Algorithms
The purpose of this repository is self-motivation and to keep track of my Machine learning, Natural Language Processing & Data Science related stuff progress
Politician-Face-Classifier
Collected images from google through web-scraping performed data cleaning, data preprocessing, exploratory data analysis, and build machine learning models such as Logistic Regression, Random Forest, and SVM(Support vector machine) achieved 88% test accuracy and deployed model to production, Used Numpy, OpenCV, SKlearn, CSS, Html, Flask, JavaScript, Selenium
awesome-knowledge-distillation
Awesome Knowledge Distillation
Hamza_Portfolio
Portfolio for my Projects
Handwritten-Digit-Recognizer
Neural Network from scratch in Python to recognize handwritten digit achieved 98.45% test accuracy and using Keras CNN(Convolutional neural network) achieved 99.25% test accuracy deployed model to production
JavaCompiler
Tokenize and Parse a String of Characters to identify if the string is a valid java program Developed java lexical and syntactical analyzer from scratch using (Compilers: Principles, Techniques, and Tools) book as a reference,
Kaggle-California-Housing-Prices-Analysis-And-prediction
A predictive analysis on california housing prices using machine learning supervised algorithms
Natural-Language-Processing-with-Disaster-Tweets
It is the first Natural Language Processing competition on Kaggle I took part in Using logistic regression with test accuracy is 77.03% using Embedding and LSTM Recurrent Neural Network test accuracy is 98%