Preparing for machine learning interviews

Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"

fast.ai Courses

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

Korean BERT pre-trained cased (KoBERT)

Implementation of some classic Machine Learning model from scratch and benchmarking against popular ML library

this repository accompanies the book "Grokking Deep Learning"

Code, exercises and tutorials of my personal blog ! 📝

Python Deep Dive Course - Accompanying Materials

Time series classification and clustering code written in Python.

The codes I made while I practiced various TensorFlow examples

A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.

My solution to the book <A collection of Data Science Take-home Challenges>

A TensorFlow implementation of DeepMind's Differential Neural Computers (DNC)

Efficient Image Captioning code in Torch, runs on GPU

A pedagogical implementation of Autograd

提供对YOLOv3及Tiny的多种剪枝版本，以适应不同的需求。

A CLI tool to convert CSV / Excel / HTML / JSON / Jupyter Notebook / LDJSON / LTSV / Markdown / SQLite / SSV / TSV / Google-Sheets to a SQLite database file.

Deep Learning Cookbox

Introduction to Deep Learning for Natural Language Processing