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clue_and_pattern

Notes On Using Data Science & Artificial Intelligence

data-analysis-and-machine-learning-projects

Repository of teaching materials, code, and data for my data analysis and machine learning projects.

ensemble-tools

features-text-extraction

Features text extraction Python for machine learning problem

kaggle

Kaggle code

machine_learning_in_finance

Built a trading algorithm in Python for the Tesla stocks returning in 39% higher returns than a simple buy and hold strategy, over a period of 2016-2018 . Designed random forest algorithm that combines CAPM, FAMA (French three factor model), Multi-Factor Linear Regression, Principal Component Analysis and Time series analysis to forecast stock prices . Generated trading signals using strategies such as Bollinger bands, Double crossover with evaluating risk and Sharpe ratio

meanshift

movie-plots-by-genre

Movie plots by genre tutorial at PyData Berlin 2016

sentimentanalysis

The code learns Support Vector Machines using 'linear' kernel to classify test data. Scikit-learn's LinearSVC provides a fast implementation for linear kernel SVMs. The features extracted from the text included the Tf-idf matrix, a commonly used method to convert text into a vetor space. Scikit-learn;s TfidVectorizer provides a complete and convenient set of functions for this. In addition to this, TruncatedSVD, another class in scikit-learn is used to approximate the feature vectors to a lower dimension (100~500 dimensions). Applying various combinations of the the different parameters (including the slack variable C in SVM, principal component size in SVD truncation and usage of monograms or bigrams in the feature extraction stage) a best estimator was selected based on

stockperformanceclassification

Keras 1D CNN on Azure ML Workbench to classify 4 week stock performance based on text in public earnings statements

tensorflow

Computation using data flow graphs for scalable machine learning

tensorflow-tutorials

TensorFlow Tutorials with YouTube Videos

wordbatch

Parallel text feature extraction for machine learning