All executed machine learning and deep learning projects at Zummit Africa
# Zummit-Africa-ML-AL-Projects
A compilation of Oluwasegun Odusina's executed machine learning and deep learning projects while at Zummit Africa as a junior data scientist.
## Table of Content:
- Supervised Machine Learning
- Unsupervised Machine Learning
- Computer Vision Deep Learning
- Deep Learning
- Team Project
- Model & Deployment
### Supervised-Machine-Learning
- Regression Models Linear, Ridge Regression, Random Forest Regressor and the XGBRegressor models to predict the housing price based on certain factors.
- Linear Regression Linear Regression model to predict the housing price based on certain factors.
- RandomForestRegressor model RandomForestRegressor model to predict the housing price of Melbourne.
- Classification models Classification Model Comparison with Red Wine Dataset using Random Forest Classifier, Support Vector Machines (SVMs), KNeighborsClassifier(KNN), Decision Tree Classifier, Naive Bayes.
- Email Classification model Classify email coming in to be either spam or not spam.
### Unsupervised-Machine-Learning
- KNeighborsClassification model Predicting heart disease with KNN GridSearchCV Hyperparameter.
### Computer-Vision-Deep-Learning
- Face Recognition model Image CLassification with VGG16 transfer learning from keras on Pinterest celebrities image dataset by Kaggle.
- Emotion Detection model Emotion Dection With FER 2013 dataset from Kaggle.
- Alexnet_Architecture Alexnet architecture with on intel_images from kaggle.
- Object Detection model Object detection with YOLO V6 on tortoise and dolphin dataset from kaggle.
- Facial Features Detecion model Facial features detecion using dlib with the shape_predictor_68_face_landmarks.dat pre-trained model.
### Deep-Learning
- CNN And SVM model Classification Dog & Cat Classification With CNN And SVM model Used Case
- MNIST Digit Classification MNIST Digit Classification With Neural Network.
### Team-Project
- Business Review Sentimental Analyser Sentimental analysis model and deploym …