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a-deep-reinforced-model-for-abstractive-summarization

Pytorch implementation for paper of "A DEEP REINFORCED MODEL FOR ABSTRACTIVE SUMMARIZATION". https://arxiv.org/abs/1705.04304

ai-for-healthcare-nanodegree-udacity

Projects and exercises for Udacity's AI for Healthcare Nanodegree. (May-Jul 2020)

aima-python

Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

aind-gridworld

Solving a 5x4 grid world problem using reinforcement learning techniques, Value Iteration and Q-Learning

aind-reinforcement

CS 188 (Introduction to Artificial Intelligence): Project 3: https://www.edx.org/courses/BerkeleyX/CS188/sp13/courseware/Week_6/Project_3_Reinforcement/

aind1e-constraint_satisfaction

Constraint Satisfaction Problem lab to solve the N-Queens problem

aind1e-simulated_annealing

Jupyter notebook exercise to check your understanding of simulated annealing

aind1p-isolation

Created an AI that beats human opponents in the game of Isolation using Minimax, Alpha-Beta Search, and Iterative Deepening.

aind1p-planning

Used logic and planning techniques to create an AI that finds the most efficient route to route cargo around the world to their respective destinations. This project used a combination of propositional logic and search along with A* heuristics to find optimal planning solutions.

aind1p-recognizer

:rocket: Built a system that can recognize words communicated using the American Sign Language (ASL) implementing Hidden Markov Models (HMMs) with model selection techniques (e.g.,BIC, DIC, and K-fold Cross Validation). :mortar_board:

aind1p-sudoku

aind2e-cnn

AIND Term 2 -- Lesson on Convolutional Neural Networks

aind2e-dl

aind2p-dog-project

Building a pipeline that can be used within a web or mobile app to process real-world, user-supplied images

aind2p-rnn

Project materials for RNN segment of AIND nanodegree

aind3e-cv-facialkeypoints

AIND, computer vision capstone project. This repo contains starting code for an end-to-end facial keypoint recognition system that relies on a combination of computer vision and deep learning techniques.

aind3e-cv-mimic

AIND Computer Vision project: Mimic Me!

aind3e-nlp

Coding exercises for the Natural Language Processing concentration, part of Udacity's AIND program.

aind3e-nlp-bookworm

A simple question-answering system built using IBM Watson's NLP services.

aind3p-nlp-capstone

:mortar_board: Building a deep neural network that functions as part of an end-to-end machine translation pipeline. :rocket:

amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

artificial-intelligence-deep-learning-machine-learning-tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! 😀)

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

bdml-bigdata-capstone-project

This reposetory includes splunk,knime,Neo4j documents and report from Big Data Capstone Project

boilerplatedappproject

Decentralized Star Notary Service. Vasucoin(VASU)

carnd-advanced-lane-lines

Built an advanced lane-finding algorithm using OpenCV for Hough Transforms and Canny edge detection, distortion correction, image rectification, color transforms, and gradient thresholding. Identified lane curvature and vehicle displacement. Detected highway lane lines on a video stream. Overcame environmental challenges such as shadows and pavement changes.

carnd-alexnet-feature-extraction

This lab guides you through using AlexNet and TensorFlow to build a feature extraction network.

carnd-behavioral-cloning

Built and trained a convolutional neural network for end-to-end driving in a simulator, using TensorFlow and Keras. Used optimization techniques such as regularization and drop out to generalize the network for driving on multiple tracks.

carnd-didi-competition

Resources for the Udacity/Didi $100k competition

carnd-e-kalman