Machine Learning Projects (Python, TensorFlow, scikit-learn, Keras)
May 2018 – Present
- Implemented several machine learning projects on Kaggle using multiple machine learning models including LR, KNN, SVM, DT, RF, XGBoost, Adaboost, GBDT, NB, NN, CNN etc.
- Please see GitHub for more details
Reproduce MTCNN (Python, TensorFlow)
Jun 2018 – Dec 2018
- MTCNN is a Multi-task cascaded convolutional network for face detection and alignment
- Built the model structure using TensorFlow and implemented the process of convert the ground truth
landmarks to tfrecord file with data enhancement
- Implemented the process of calculating the loss of classifications, bounding boxes, and landmarks,
finally achieved 93% accuracy
Build Face Recognition website (Python, TensorFlow)
Dec 2018 – Jan 2019
- A face recognition website that can compare whether the person in the two pictures is the same person using python Flask as the user interface.
- Use pre-trained MTCNN to detect the face position in pictures and use pre-trained FaceNet to calculate the distance between two faces.
Optimize DIVA Model (Python, TensorFlow)
Aug 2017 – Dec 2017
- Optimized the hyperparameters selection in DIVA model (divergent auto-encoder model of category learning, an artificial neural network that uses reconstructive learning to solve N-way classification tasks) by using hyperopt approach. Shorten the search time at least doubled.