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allen-ai-science-challenge

The Allen Institute for Artificial Intelligence (AI2) is working to improve humanity through fundamental advances in artificial intelligence. One critical but challenging problem in AI is to demonstrate the ability to consistently understand and correctly answer general questions about the world. https://www.kaggle.com/c/the-allen-ai-science-challenge

asthma_risk_factor

comorbidity_index

Python package for comorbidity index calculation

coursera-ai-for-medicine-specialization

Programming assignments, labs and quizzes from all courses in the Coursera AI for Medicine Specialization offered by deeplearning.ai

coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks;

coursera-sna

Social Network Analysis. Lecture Materials & Video (march 2013)

crowdfunding

csberkeley_cs61b

data_structures_and_algorithms_in_python

deepdream

deeplearning.ai-pytorch

PyTorch Implementations of Coursera's Deep Learning(deeplearning.ai) Specialization

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

exdata_plotting1

Plotting Assignment 1 for Exploratory Data Analysis

extracting-signal-from-social-media-text

identifying-depression

Identifying depression based on texts

imbalanced-learn

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

kmeans-and-kernel-kmeans

####Goals#### * Implement the following clustering algorithms: K-means and Kernel K-means. * Implement the following supervised clustering evaluation metrics: purity and NMI.

kmp

Knuth–Morris–Pratt algorithm

leetcode

lstm

Minimal, clean example of lstm neural network training in python, for learning purposes.

machine-learning-and-deep-learning

mis-536-lab-s19

MIS 536 Lab Spring 2019

mis536-public

Resources for Fall 2020 MIS536

modules

neural_networks_deep_learning

nlp_course

YSDA course in Natural Language Processing

pima_report

pyspark_training

python_lib

python_machine_learning