Applications in learning, training, scientific research, and knowledge discovery.
Objective Observe and improve the results of running regression algorithms (Random Forest Regression, Support Vector Regression, Artificial Neural Networks) on daily macroeconomic data to predict daily currency prices for GBPUSD, EURUSD and…
First M87 Event Horizon Telescope Results. III. Data Processing and Calibration Abstract We present the calibration and reduction of Event Horizon Telescope (EHT) 1.3 mm radio wavelength observations of the supermassive black…
Often the hardest part of solving a machine learning problem can be finding the right estimator (algorithm) for the job. Different estimators are better suited for different types of data and different…
Pandas is a powerful python library for data manipulation. It requires limited query level optimisation as its functions can perform rapid data manipulation and analysis on the entire data set. Below is…
Data Wrangling(preprocessing, prep, etc) is the most important and time consuming part of any data science project. Depending on the quality of data sources, 50%-60% of the initial effort is spent in…
Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, etc. One of the oldest and most…
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. https://www.anaconda.com/ Spyder is a powerful scientific environment written in Python,…
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 foundations for statistical methods that are useful in many applications.…
Stanford Lecture Collection | Natural Language Processing with Deep Learning (Winter 2017). https://www.youtube.com/playlist?list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6
Very good free YouTube tutorials on Linear algebra - matrices, vectors, eigenvectors, etc. Essence of linear algebra. A geometric understanding of matrices, determinants, eigen-stuffs and more. Home page: https://www.3blue1brown.com/ https://www.youtube.com/watch?v=fNk_zzaMoSs&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab
Machine Learning A-Z™: Hands-On Python & R In Data Science Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included. Created by Kirill Eremenko, Hadelin…
Abstract - Semantic word spaces have been very useful but cannot express the meaning of longer phrases in a principled way. Further progress towards understanding compositionality in tasks such as sentiment detection…
