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kaushikmanikonda/README.md

Hi there 👋 I am Kaushik Manikonda!

I am an Aggie, a Machine Learning Researcher, an Industrial Engineer, a Petroleum Engineer, an Astrophysicist, and a Data Scientist all in one.

I am currently learning and applying machine learning algorithms/techniques to solve well control problems in offshore oil/gas/geothermal drilling. So, most of my repositories are related to machine learning, python, R, SQL, and Data Analysis.

I am still gradually reorganizing all my repositories with better naming schemes, and folder placement. So, Please do not mind any unorganized folders or files with esoteric names.

An Aggie does not lie, cheat, or steal, or tolerate those who do!

Some of my repositories are also directly related to coursework at Texas A&M university, College Station. Please keep the Aggie code of honor in mind when you are downloading and using my code/applications.

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  1. AdvPredictiveModeling_withPython AdvPredictiveModeling_withPython Public

    Forked from UCIDataScienceInitiative/AdvPredictiveModeling_withPython

    Jupyter Notebooks for Adv. Predictive Modeling Course

    Jupyter Notebook

  2. Data-Analysis-Using-Python-OCNG_669_Geosciences Data-Analysis-Using-Python-OCNG_669_Geosciences Public

    Python for Geosciences: Basic python, Numpy, Matplotlib, Pandas, Data analysis, Data Visualization

    Jupyter Notebook 1

  3. Databases-and-Big-Data-Tools_STAT_624 Databases-and-Big-Data-Tools_STAT_624 Public

    Python, Parallel R, SQL, SQL Databases, No SQL Databases, Linux and Shell Scripting, Introduction to OpenMP, Compiling, Optimization, Vectorization, Data Management and GIT, Introduction MPI, Intro…

    Fortran

  4. Design-and-Analysis-of-Industrial-Experiments_ISEN_616 Design-and-Analysis-of-Industrial-Experiments_ISEN_616 Public

    Designing Industrial Experiments, one-way, and two-way ANOVA analysis, Experimental design principles (Replication, Randomization, and Blocking), Parameter Estimation, Sample Variance

    R

  5. Industrial-Data-Analytics-and-Machine-Learning_ISEN_613 Industrial-Data-Analytics-and-Machine-Learning_ISEN_613 Public

    Data Analytics and Machine Learning in R. Linear-regression, Logistic-regression, Hierarchical-clustering, Boosting, Bagging, Random-forests, K-means-clustering, K-nearest-neighbors (K-N-N), Tree-p…

    R

  6. machine-learning-for-trading machine-learning-for-trading Public

    Forked from stefan-jansen/machine-learning-for-trading

    Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

    Jupyter Notebook