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Notes and project source code from my training "Data Science & Engineering - Fullstack" at JEDHA

Main topics

  • Python Programming
    • classes, git
  • Exploratory Data Analysis
    • numpy
    • pandas
    • plotly
  • Data Collection and Management
    • HTTP
    • API
    • Scraping
    • AWS S3 Boto3
    • AWS RDS SQLAlchemy
  • Big Data
    • RDDs (Resilient Distributed Datasets)
    • Databricks, Tidy, SparkSQL, pgAdmin
    • Spark, PySpark
    • AWS RedShift
  • Supervised Machine Learning
    • Sklearn
    • Linear Regression
    • Regularization and Hyperparamter optimization
    • Logistic Regression
    • Decision Tree, Random Forest
    • SVM support vector machine
    • Ensemble Learning AdaBoost XGBoost
    • Model Selection et Evaluation
    • Times Series
  • Unsupervised Machine Learning
    • kMeans
    • DBSCAN
    • PCA
    • NLP Natural Language Processing for unsupervised learning
    • Topic Modeling
  • Deep Learning
    • Gradient Descent
    • Neural Networks
    • TensorFlow, Keras
    • CNN Convolutiional Neural Network
    • Transfer Learning
    • GAN
    • Word Embedding, Word2Vec
    • RNN Recurrent Neural Network
    • Encoder Decoder
    • Attention
  • Deployment
    • Local Dev
    • Dashboard Streamlit
    • Docker
    • Deploy to Heroku
    • MLFlow
    • Package & Serve models
    • API for your model ...