My Github contains my notes, codes and projects in my journey of DS, ML and DeepLearning. For more information about my mathematical research, please go to this page; see also my CV and my Linkedin
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6 projects concernant Tabular Datasets (Link). Some keywords:
- Manipulation, Clearning, Visualisation, Preprocessing
- Frameworks: Scikit Learn, Seaborn, Pandas, Numpy
- Algorithms Logistic Regression, KNN, Linear and Kernel SVM, RandomForest, AdBoost, GradienBoosting, Xgboost
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3 Projects about image classification (Link)
- Humans and Horses; Dogs and cats; Rocks, scissors and paper
- Framework: Keras/Tensorflow
- Technical keywords: Convnet, DataAugmentation, Load image from folders, Transfer learning
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1 Project about single object Detection (Link)
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1 Project about image classification and single object Detection (Link)
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1 Project about Text analyses with several aproches (Link)
- Scikit Learn, NLTK
- Sequence model (TensorFlow Framework)
A personal summary of codes for DS, ML and DL (Link)
- Datascience Career Track (DataCamp) (Certificat)
- Deep Learning Specialization (DeepLearning.AI and Coursera) (Link)
- TensorFlow in Practics Specialization (DeepLearning.AI and Coursera) (Link)
- Tensorflow: Deployement and Pipiline Specialization (in progress)
- TensorFlow: Advanced Techniques Specialization (in progress)