In this project, we will download historical S&P 500 index data from Yahoo Finance, performs some preliminary exploratory data analysis and manipulations, and then we will apply a Random Forest model to predict whether the index will go up or down on the next trading day based on the past Lire la suite…
In this project, we will show some workflows that are useful for EELS data analysis. We will cover multiple topics such as background removal, Hartree-Slater cross section function, low loss analysis (band gap, plasmon shift calculations), high loss analysis (L2/L3 ratio analysis) and so on. Data loading and Background substraction Lire la suite…
Development of new tools for the Neural Amp Modeler developed by Steven Adkinson. Neural Amp Modeler is an open-source project that uses deep learning to create models of guitar amplifiers and pedals with state of the art accuracy. Under construction…
Analyzis of satellite data using Neural Networks Under construction…
In this project, we have used multiple Python libraries to do a full analysis of High Resolution Scanning Transmission Electron Microscope (HRSTEM) images of LSMO/STO Perovskites. In this particular project, we will use atomap module for the detection of atoms in a HRSTEM image and then connect the atoms with Lire la suite…
Analysis of the socio-cultural influence on the voting result of a referendum Introduction Analysis of the socio-cultural influence on the voting result of a referendum. In this project, we were given one dataset named ‘Referendum.csv’ representing the voting results by municipality in France from mock referendum that took place in Lire la suite…
Shot success predictions in the NBA using ML and Deep Learning Introduction The National Basketball Association (NBA) is one of the most popular sports leagues in the world, with millions of fans across the globe. Numerous factors have contributed to the NBA’s rise in popularity over the years. Among others, Lire la suite…