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Stars83
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Global Rank 237,100 (Top 9 %)
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Followers 14
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Registered over 4 years ago
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Most used languagesJupyter Notebook69.2 %R15.4 %HTML15.4 %
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Location 🇩🇪 Germany
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Country Total Rank 17,555
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Country RankingJupyter Notebook376R560HTML1,814
Top repositories
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EDHEC_Investment-Management-with-Python-and-Machine-Learning-
Jupyter notebooks and data files of the new EDHEC specialization on quantitative finance (completed Aug 2022)Jupyter Notebook
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HKUST-Python_and_Statistics_for_Financial_Analysis
The Hong Kong University of Science and Technology course "Python and Statistics for Financial Analysis" by Prof. Xuhu Wan on CourseraJupyter Notebook
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Stanford-StatisticalLearning
Stanford Online course STATSX0001 "Statistical Learning" follows closely the sequence of chapters in the course text "An Introduction to Statistical Learning, with Applications in R" (James, Witten, Hastie, Tibshirani - Springer 2013). Trevor Hastie Professor of Statistics and of Biomedical Data Sciences, Stanford University, and Robert Tibshirani Professor of Biomedical Data Science and Statistics, Stanford UniversityHTML
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UCSanDiego_MicroMasters_DataScience-ProbabilityandStatistics
The University of California, San Diego, course DSE210x "Probability and Statistics in Data Science using Python" (Winter 2018): Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. Part 2 of »Data Science« MicroMasters® on edX, Instructors: Alon Orlitsky and Yoav Freund, Professors of CS and Engineering, University of California San Diego.Jupyter Notebook
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Econometrics_Methods_and_Applications
Erasmus University Rotterdam course »Econometrics: Methods and Applications« by Prof. Philip Hans Franses and others (completed Jan. 2023)R
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Stanford-BUS139W-DataDrivenMarketing
Stanford Continuing Studies course "Data-Driven Marketing" by Angel Evan, Consultant. Completed Winter 2017-2018
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UCSanDiego_MicroMasters_DataScience-Python4DS
The University of California, San Diego, course DSE200x "Python for Data Science" (Summer 2018): Learn to use powerful, open-source, Python tools, including Pandas, Git and Matplotlib, to manipulate, analyze, and visualize complex datasets. Part 1 of »Data Science« MicroMasters® on edX. Instructors: Ilkay Altintas, Chief Data Science Officer, San Diego Supercomputer Center (SDSC) and Leo Porter, Assistant Teaching Professor, Computer Science and Engineering at University of California San DiegoJupyter Notebook
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Stanford-BUS123-W-ValueInvesting-
This Stanford Continuing Studies course follows the textbooks Marshall (2017): "Good Stocks Cheap: Value Investing with Confidence for a Lifetime of Stock Market Outperformance"" (ISBN 125983607X). Instructor: Kenneth Jeffrey Marshall, Stockholm School of Economics
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ICL-Mathematics-for-Machine-Learning
Imperial College London »Mathematics for Machine Learning«. A sequence of 3 courses on the prerequisite mathematics for applications in data science and machine learning. (1) Linear Algebra (2) Multivariate Calculus and (3) Principal Component Analysis (completed Sept. 10th, 2018)Jupyter Notebook
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Stanford-BUS150W-FinancialModeling_OptimalAssetAllocation
The final project for Stanford Continuing Studies course BUS 150 W "Financial Modeling and Business Decisions" by Iddo Hadar, Summer 2017. This online course provides students with the methods and the mindset to make complex financial and economic decisions, by framing them as analytical models and using Microsoft Excel spreadsheets to solve them.
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TUe-Improving_Statistical_Questions
Eindhoven University of Technology (TU/e) course "Improving Your Statistical Questions" by Daniël Lakens on Coursera (completed Dec 2022).R
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Recommendations_with_IBM
Project No.3 in the Udacity Data Scientist Nanodegree Program. Will build a recommendation engine, based on user behavior and social network in IBM Watson Studio’s data platform, to surface content most likely to be relevant to a user.Jupyter Notebook
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Udacity_DataAnalystNanodegree-DataVisualization
Project No. 5 in the Udacity Data Analyst Nanodegree. Analyse the Risk and Return characteristics of Prosper consumer loans 2006-2014. (completed Mar 2020)Jupyter Notebook
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StackOverflowDeveloperSurvey
Project No.1 in the Udacity Data Scientist Nanodegree. Analyse the StackOverflow survey data and publish a Blog Post on Medium.Jupyter Notebook
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UCSanDiego_MicroMasters_DataScience-BigDataAnalyticsUsingSpark
The University of California, San Diego, course DSE230x "Big Data Analytics Using Spark" (Summer 2019): Learn how to analyze large datasets using Jupyter notebooks, MapReduce and Spark as a platform. Part 4 of the »Data Science« MicroMasters® Program on edX. Instructor: Yoav Freund, Professor of CS and Engineering, University of California San Diego.
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Disaster-Response-Pipeline-
Project No.2 (Data Engineering) in the Data Scientist Nanodegree program. Build a machine learning pipeline to categorize emergency messages based on the need communicated by the sender.Jupyter Notebook
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UCSanDiego_MicroMasters_DataScience-MachineLearningFundamentals
The University of California, San Diego, course DSE220x "Machine Learning Fundamentals" (Spring 2019): Understand machine learning's role in data-driven modelling, prediction, and decision-making. Part 3 in the »Data Science« MicroMasters® on edX, Instructor: Sanjoy Dasgupta, Professor of CS and Engineering.
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Sparkify
Capstone Project in the Udacity Data Scientist Nanodegree program. We manipulate large and realistic datasets with Spark to engineer relevant features for predicting churn. We'll learn how to use Spark MLlib to build machine learning models with large datasets, far beyond what could be done with non-distributed technologies like scikit-learn.HTML
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