Monthly Asset price relationship to Macroeconomic Data
Legal Disclaimer – This research is not an
investment advisory or a sales pitch.
Objective
Identify the...
KDnuggets – Top Data Science, Machine Learning Methods Used, 2018/2019
Very interesting post by KDnuggets on machine learning methods being used. Lot of increase in usage for deep learning neural network algorithms....
Daily Currency Price prediction using Daily Macroeconomic Data by applying Regression (Random Forest, SVR,...
Objective
Observe and
improve the results of running regression algorithms (Random Forest Regression,
Support Vector Regression, Artificial Neural Networks) on daily...
First image of a Black Hole built using Python
First M87 Event Horizon Telescope Results. III. Data Processing and Calibration
Abstract
We present the...
ML Map – Choosing the right algorithm for your problem
Often the hardest part of solving a machine learning problem can be finding the right estimator (algorithm) for the job.
Pandas for Data Wrangling – tutorial, cheat sheet
Pandas is a powerful python library for data manipulation. It requires limited query level optimisation as its functions can perform rapid data...
Data Wrangling – preprocessing
Data Wrangling(preprocessing, prep, etc) is the most important and time consuming part of any data science project. Depending on the quality of...
Open source Data science libraries – AI, ML, NLP
Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including...
Open source Data science Tools – Anaconda, Spyder, Python
The open-source Anaconda Distribution is the easiest way to perform Python/R data science and machine learning on Linux, Windows, and Mac OS X....
Youtube – MIT OpenCourseWare – Statistics lecture series
MIT 18.650 Statistics for Applications, Fall 2016 View the complete course: http://ocw.mit.edu/18-650F16 Instructor: Philippe Rigollet This course offers an in-depth the theoretical...
