Arbaz (arbazkhan971)

arbazkhan971

Geek Repo

Company:Lineupx

Location:Mumbai

Home Page:https://lineupx.com/

Twitter:@arb5z

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Arbaz's repositories

HumanActivityRecognition

This project is to build a model that predicts the human activities such as Walking, Walking_Upstairs, Walking_Downstairs, Sitting, Standing or Laying.

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candis

:ribbon: A data mining suite for gene expression data.

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Cifr-datasets-for-object-reconigation

In this project i had built cnn model for object recognition on famous dataset cifr

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co-learning-lounge

Welcome to the one point community-driven encyclopedia for anything in technology.

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course-nlp

A Code-First Introduction to NLP course

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Data-Structures-and-Algorithms

Notes on data structures and algorithms for competitive programming

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deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

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Delving-deep-into-GANs

:chart_with_upwards_trend: A curated list of Generative Adversarial Networks (GANs) resources sorted by reputation

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fastbook

Draft of the fastai book

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MNIST-dataset-for-handwritten-digit-recognition

In this post i had discovered how to develop a deep learning model to achieve near state of the art performance on the MNIST handwritten digit recognition task in Python using the Keras deep learning library

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NLP-progress

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

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rasa

đź’¬ Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants

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stanford-cs-230-deep-learning

VIP cheatsheets for Stanford's CS 230 Deep Learning

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SyferText

A privacy preserving NLP framework

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sympy-live

The source for the code at live.sympy.org

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Technical-Interview-Megarepo

Study materials for SE/CS technical interviews

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tv-marketing-data

In this example we will consider sales based on 'TV' marketing budget. In this notebook, we'll build a linear regression model to predict 'Sales' using 'TV' as the predictor variable.

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