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anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

applied_data_science_with_python

Code and materials from "Applied Data Science with Python" Specialization by University of Michigan on Coursera.

awesome-time-series

Resources for working with time series and sequence data

awesome-ts-anomaly-detection

List of tools & datasets for anomaly detection on time-series data.

cracking-the-data-science-interview

A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 175 universities.

deep-learning-in-phm

Deep learning in PHM，Deep learning in fault diagnosis，Deep learning in remaining useful life prediction

deep-learning-time-series

List of papers, code and experiments using deep learning for time series forecasting

deepadots

Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".

dl-4-tsc

Deep Learning for Time Series Classification

dtaidistance

Time series distances: Dynamic Time Warping (DTW)

electric-vehicle-battery-range-prediction

Predict remaining useful lifetime of an electric car accurately to help drive owner satisfaction and future purchases. This solution comprises analyzing the vast quantity of telemetry data over time and building a Machine Learning model to predict the remaining useful life(RUL) of an electric vehicles EVs at each point in time of the operation of said vehicle. The customer is the largest automotive manufacturing company in India, by market share. The customer designs, builds, and delivers electric vehicles (EVs).

etc3550slides

Slides for a forecasting course based on "Forecasting: Principles and Practice"

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

introduction-to-data-science-in-python

Assignments related to Introduction to Data Science in Python coursera course.

k-nearest-neighbors-with-dynamic-time-warping

Python implementation of KNN and DTW classification algorithm

kats

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

learn-python

📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.

learning-time-series-python

Notes of Udemy course on Time Series

leetcode

LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)

leetcode-1

My solutions for LeetCode problems

leetcode_company_wise_questions

This is a repository containing the list of company wise questions available on leetcode premium

machine-learning-with-python

Python code for common Machine Learning Algorithms

neural-networks-and-deep-learning

Code samples for my book "Neural Networks and Deep Learning"

predict-remaining-useful-life

Predict remaining useful life of a component based on historical sensor observations using automated feature engineering

predictive-maintenance

Data Wrangling, EDA, Feature Engineering, Model Selection, Regression, Binary and Multi-class Classification (Python, scikit-learn)

prog_algs

Prognostics Algorithms Package

prog_models

Prognostics Models Package

python-for-everybody-specialization

rul-net

Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine