aakashsinha19 Goto Github PK
Name: Aakash Sinha
Type: User
Company: Business Technology Solutions Associate Consultant @ ZS
Bio: Cogntive Sense Activated!
Location: Pune, Maharashtra
Name: Aakash Sinha
Type: User
Company: Business Technology Solutions Associate Consultant @ ZS
Bio: Cogntive Sense Activated!
Location: Pune, Maharashtra
These are the instructions for "100 Days of ML Code" By Siraj Raval on Youtube
Machine Learning is the most transformative technology of our time. Whether its helping us discover new drugs for major diseases, fighting fraud, generating music, improving supply chain efficiency, the list of applications are truly endless. I am taking up the 100 Days of ML Code as a committment to better my understanding of this powerful tool by dedicating at least 1 hour of my time everyday to studying and/or coding machine learning for 100 days.
Implementation of Image Segmentation and Classification using Python on Tensorflow v0.12 and wrapper Slim, neural net VGG-16s, Scikit Image Library and Inception. The updated version of Aspectus contains custom made sticker batches for Telegram using the output.png file
This Reporistory contains Study Materials and link for various Online Courses / Certifications. Hope this helps everyone. Cognitive Sense Activated!
This repository contains the source code for the semantic image segmentation method described in the ICCV 2015 paper: Conditional Random Fields as Recurrent Neural Networks. http://crfasrnn.torr.vision/
Data Science
The Leek group guide to data sharing
Deep Learning Specialization by Andrew Ng on Coursera.
We will design a fast MapReduce algorithm for Monte Carlo approximation of personalized PageRank vectors of all the nodes in a graph. The basic idea is very efficiently doing single random walks of a given length starting at each node in the graph. More precisely, we design a MapReduce algorithm, which given a graph G and a length λ, outputs a single random walk of length λ starting at each node in G. We will show that the number of MapReduce iterations used by our algorithm is optimal among a broad family of algorithms for the problem, and its I/O efficiency is much better than the existing candidates. We will then show how we can use this algorithm to very efficiently approximate all the personalized PageRank vectors. Our empirical evaluation on real-life graph data and in production MapReduce environment shows that our algorithm is significantly more efficient than all the existing algorithms in the MapReduce setting.
To Develop accurate prediction models (like Naiive Bayes, Logistic Regression or Decision Tress) for flight delays using a generic database to overcome the difficulties faced by passenger travelling in huge numbers daily and come up with an optimized result.
A library to learn Algorithms and Data Structures for newbies
Classify whether an image is of a Spiral or an Elliptical Galaxy using Transfer Learning (Tensorflow)
A library for transfer learning by reusing parts of TensorFlow models.
Uncovering common themes from a large number of unor- ganized search queries is a primary step to mine insights about aggregated user interests. Common topic model- ing techniques for document modeling often face sparsity problems with search query data as these are much shorter than documents. We present two novel techniques that can discover semantically meaningful topics in search queries: i) word co-occurrence clustering generates topics from words frequently occurring together; ii) weighted bigraph cluster- ing uses URLs from Google search results to induce query similarity and generate topics. We exemplify our proposed methods on a set of Lipton brand as well as make-up & cos- metics queries. A comparison to standard LDA clustering demonstrates the usefulness and improved performance of the two proposed methods. keywords: search queries, topic clustering, word co- occurrence, bipartite graph, co-clustering.
Short Codes for automating some boring stuff using Python :octocat: :beer: :zzz:
We often face naive problems in our daily life and wish if there was some way to automate or ease those tasks. Well, here it is! This repository has micro codes written in Python to ease such tasks.
ML Sessions Code Repository
O2 leverages Google’s search capabilities to implement a semantic search. The core idea in o2 is to allow a user to find documents based on the Intent within the document. For example a user may want to search for an advanced or a basic document on Java programming. The idea of “advanced” or “basic” is represented as an intent graph. A set of terms that if present in the document, reinforces the fact that the document is indeed “basic” or “advanced” in nature. In addition to intents, o2 uses a vocabulary of terms around which these indexes are to be built. For example, o2 can work with the complete set of topics, a student learns in Java and then act as a semantic search engine for these topics.
scikit-learn: machine learning in Python
Implementing SHARQ protocols in openLTE and study performance variation with Maximum HARQ rounds.
A generic chat bot made using Watson Conversation API.
Coding Practice for Summer 2017
Computation using data flow graphs for scalable machine learning
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.