Anmol Singhai's repositories

Prediction-of-Future-location-using-Hidden-Markov-Model

Prediction of Future location using Hidden Markov Model

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TensorFlow-Tutorials

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

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Algorithms

A collection of algorithms and data structures

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cal.com

Scheduling infrastructure for absolutely everyone.

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Convolutional_neural_network

This is the code for "Convolutional Neural Networks - The Math of Intelligence (Week 4)" By Siraj Raval on Youtube

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Deep-Learning-in-Python

Hands-on, practical knowledge of how to use neural networks and deep learning with Keras 2.0

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educative.io_courses

this is downloadings of all educative.io free student subscription courses as pdf from GitHub student pack

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first-contributions

🚀✨ Help beginners to contribute to open source projects

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HMM

Python Hidden Markov Models framework

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Install-OpenCV

shell scripts to install different version of OpenCV in different distributions of Linux

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keras

Deep Learning library for Python. Runs on TensorFlow, Theano, or CNTK.

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laneDetetction

Python implementation to detect lanes on road for driverless cars

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learntris

a test suite to help you implement a famous falling blocks game

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LeetCode-Questions-CompanyWise

Contains Company Wise Questions sorted based on Frequency and all time

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lstm-siamese-text-similarity

⚛️ It is keras based implementation of siamese architecture using lstm encoders to compute text similarity

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playing-games-with-python

Reinforcement Learning.https://s3.gifyu.com/images/games.gif

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tensorflow

Computation using data flow graphs for scalable machine learning

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TreeStructure

Table Extraction Tool

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VSE-C

Implementation of our paper "Learning Visually-Grounded Semantics from Contrastive Adversarial Samples" at COLING 2018.

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WebRTC-Scalable-Broadcast

This module simply initializes socket.io and configures it in a way that single broadcast can be relayed over unlimited users without any bandwidth/CPU usage issues. Everything happens peer-to-peer!

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word-embeddings-from-scratch

Creating word embeddings from scratch and visualize them on TensorBoard. Using this trained embeddings in Keras.

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