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Name: Hitashu Kanjani
Type: User
Bio: interested in DS and ML
Location: Boston , Massachusetts
Name: Hitashu Kanjani
Type: User
Bio: interested in DS and ML
Location: Boston , Massachusetts
data science and machine learning
A course on causal machine learning.
Pneumonia is a very common disease. It can be either: 1) Bacterial pneumonia 2) Viral Pneumonia 3) Mycoplasma pneumonia and 4) Fungal pneumonia. This dataset consists pneumonia samples belonging to the first two classes. The dataset consists of only very few samples and that too unbalanced. The aim of this kernel is to develop a robust deep learning model from scratch on this limited amount of data. We all know that deep learning models are data hungry but if you know how things work, you can build good models even with a limited amount of data
The original work that we have tried to replicate was done by a team of researchers from Tencent Technology, the Chinese University of Hong Kong, and Nankai University who proposed a novel method to address the issue of improving training deep neural networks (DNN). Their work is published through the paper "Rethinking the Usage of Batch Normalization and Dropout in the Training of Deep Neural Networks" (Chen et al., 2019) which proposes a marriage of 2 commonly used techniques – Batch Normalisation and Dropout, to achieve input whitening that neither method could otherwise achieve independently.
A collection of easy-to-understand guides to programming tools
Capstone Project [Walmart Sales Forecasting]
Creating a repository of all ML projects done over time for learning purposes
Machine Learning algorithm implementations from scratch.
Automatic activity recognition systems aim to capture the state of the user and its environment by exploiting heterogeneous sensors, and permit continuous monitoring of numerous physiological signals, where these sensors are attached to the subject's body. This can be immensely useful in healthcare applications, for automatic and intelligent daily activity monitoring for elderly people. The Human Activity Recognition database was built from the recordings of 30 study participants performing activities of daily living (ADL) while carrying a waist-mounted smartphone with embedded inertial sensors. The objective is to classify activities into one of the six activities performed.
Some fun and useful projects with Python
https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1
Enhanced search results of clinical trial records based on user query utilizing taxonomy of Medical SubHeadings by providing keywords and document recommendations. Dataset was taken from clinicaltrials.gov
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.