آموزش علم داده با پایتون (هوافضا) Python for Data Science and Machine Learning

-Environment set-up and installation

-Jupyter Notebooks

-Optional virtual environment

-Python crash course

-Numpy(arrays, indexing, operations)

-Pandas(series, dataframes, missing data, groupby, merging joining & concatenating, operations, data input & output)

-Data Visualization(Matplotlib)

-Matplotlib exercises

-Seaborn(distribution plots, categorical plots, matrix plots, regression plots, grids, style & color)

-Pandas built-in data visuallization

-Plotly & Cufflinks

-Geographical plotting(choroplth maps)

-projects(calls, finance)

-Introduction to Machine Learning(regression, bias variance trade-off, logistic regression theory, KNN, Decision tree & random forest, SVM, K-means algorithm,  PCA, recommender system, NLP)

-Big data overview(spark, AWS account set-up, EC2 instance set-up, PySpark set-up, lambda expression, RDD transformations & actions, Neural network theory)

-Deep Learning overview(TensorFlow basics installations & basics, MNIST with multi-layer perceptron, contriblearn)

-TensorFlow project