sharomin Goto Github PK
Name: saeed shoaraye nejati
Type: User
Company: Morgan Stanley
Bio: Java / Python Developer Machine Learning & Deep learning Eng
Location: Canada
Name: saeed shoaraye nejati
Type: User
Company: Morgan Stanley
Bio: Java / Python Developer Machine Learning & Deep learning Eng
Location: Canada
In this project, we attempt to reproduce and improve the results achieved by Yoon Kim (2014), in [1] with no published code. We implement the proposed models in his paper, which describes sentence classifiers using CNN on top of pre-trained word vectors, Word2Vec. Classification in [1], is performed on multiple datasets, with static and minimally fine-tuned Word2Vec, feeding a single layer CNN. To improve the state-of-the-art, both static and fine-tuned word vectors are used in 2 separate channels to classify sentences[1]. In this work, we simplify Kim’s approach and instead focus only on the use of different kernel sizes with parallel layers. We see that the skill of the model on the unseen test dataset was very impressive, achieving 89%, which is above the skill of the model reported in the 2014 paper. We observed, fine-tuning the pre-trained vectors for specific task improves accuracy over static vectors, and we were able to reach accuracy mentioned in [1] for MR dataset.
pickle to csv and csv to pickle transition in Python
Sentiment analysis on IMDb movie reviews
In this project, I have developed models to predict the sentiment of IMBD reviews. IMDB is a popular website and database of movie information and reviews (https://www.imdb.com/). The goal is to classify IMBD reviews as positive or negative based on the language they contain. This project was done for competing with other groups in www.kaggle.com to achieve the best accuracy in a competition.
Machine Learning mini project 3
mnist competition submission repo for Tensorflow KR group
Image Processing Project which the goal was to perform an image analysis prediction challenge. The task is based upon the MNIST dataset (https://en.wikipedia.org/wiki/MNIST_database). The original MNIST contains handwritten numeric digits from 0-9 and the goal is to classify which digit is present in an image. Here, I worked with a Modified MNIST dataset. In this modified dataset, the images contain more than one digit and the goal was to find which number occupies the most space in the image. Each example is represented as a 64 × 64 matrix of pixel intensity values (i.e., the images are grey-scale not color).
In this project we will use linear regression to predict the popularity of comments on Reddit. Reddit (www.reddit.com) is a popular website where users can form interest-based communities, post content (e.g., images, links to news articles), and participate in thread-based discussions.
Back-End API for renoViva webApp
My Personal website
A declarative, efficient, and flexible JavaScript library for building user interfaces.
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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.
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A server is a program made to process requests and deliver data to clients.
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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.