nick-ythink Goto Github PK

100-days-of-ml-code

100 Days of ML Coding

academy

Ray tutorials from Anyscale

ai-introduction

Course files for AI Introduction course

arcgis-python-api

Documentation and samples for ArcGIS API for Python

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! 😀)

autolearn

AutoLearn, a domain independent regression-based feature learning algorithm.

awesome-automl-papers

A curated list of automated machine learning papers, articles, tutorials, slides and projects

awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

awesome-public-datasets

A topic-centric list of HQ open datasets. PR ☛☛☛

awesome-random-forest

Random Forest - a curated list of resources regarding random forest

best-programming-languages-for-machine-learning

This is the code for "Best Programming Languages for Machine Learning" By Siraj Raval on Youtube

bluemix-python-sample-twitter-influence-app

Bluemix sample app written in Python that uses the Klout and Twitter API's to analyze the influence of individual twitter usernames

chatgpt_trading_bot

This is the code for the "ChatGPT Trading Bot" Video by Siraj Raval on Youtube

cheatsheets-ai

Essential Cheat Sheets for deep learning and machine learning researchers

classification_models

Classification models trained on ImageNet. Keras.

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; (v) Sequence Models

data-science

:bar_chart: Path to a free self-taught education in Data Science!

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

data_science_for_all

Code and resources for my blog and articles to share Data Science and AI knowledge and learnings with everyone

datasciencespcoursenotes

Compiled Notes for all 9 courses in the Coursera Data Science Specialization

deep-learning

Projects include the application of transfer learning to build a convolutional neural network (CNN) that identifies the artist of a painting, the building of predictive models for Bitcoin price data using Long Short-Term Memory recurrent neural networks (LSTMs) and a tutorial explaining how to build two types of neural network using as input the MNIST dataset, namely, a CNN using Keras and a fully-connected network using TensorFlow.

deep-learning-books

deep-learning-models

Keras code and weights files for popular deep learning models.

dp-203-data-engineer

dsi-5-submission

earning-manipulation

Earning manipulation for banking customers is predicted using Logistic Regression

earning-manipulation-using-stepwise-logistic-regression

Predicting earning manipulations using Stepwise Logistic Regression with Data Cleaning

evidently

Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b

featuretools

An open source python framework for automated feature engineering

fraud-prediction

Data Science Case Study