- Physicist, Msc in AI π
- Fluent in Python. Libraries: Numpy, Pandas, Matplotlib, Tensorflow, Keras, Pytorch, SciKit, Stable Baselines3, Spacy, Nltk, Opencv2, Tensorboard... π₯οΈ
- Deep Learning Skills (Convolutional Neural Networks, Recurrent Neural Networks, Deep Reinforcement Learning, Generative Adversarial Networks, Transformers, Neural Style Transfer, Data Augmentation...) π€
- Supervised Learning Skills (Random Forest, Support Vector Machines, Naibe Bayes...) β
- Unsupervised Learning Skills (Clustering, Principal Component Analysis, Outlier Detection...) βοΈ
- Digital Image Processing (Image Filtering, Kernels, SIFT, Object Detection, Image Segmentation) πΌοΈ
-Natural Language Processing (Twitter Sentiment Analysis, Word2Vec, Corpus Based Supervised Learning) π
- Analysis and Data Visualization π
- Maths and Physics Skills π