Kyubyong / up_and_running_with_Tensorflow
A simple tutorial of TensorFlow + TensorFlow / NumPy exercises
☆13Updated 7 years ago
Related projects ⓘ
Alternatives and complementary repositories for up_and_running_with_Tensorflow
- list of Pycon2016 session related with ML☆22Updated 8 years ago
- ☆18Updated 7 years ago
- A talk on TensorFlow debugging -- REPOSITORY MOVED TO:☆8Updated 7 years ago
- RNN Approaches to Integer Sequence Learning--the famous Kaggle competition☆27Updated 7 years ago
- Demo codes in our presentation about MXNet in AWS Seoul Summit 2017☆13Updated 7 years ago
- Deep learning study in Gluon 2nd edition☆23Updated 5 years ago
- Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book a…☆12Updated 8 years ago
- ☆16Updated 6 years ago
- Collection of (unfinished) notebooks☆14Updated 4 years ago
- ☆21Updated 8 years ago
- Predicting sales with Pandas☆15Updated 9 years ago
- ☆26Updated 8 years ago
- A super simple way to do distributed hyperparameter tuning with Keras and Mongo☆30Updated 7 years ago
- Visual Question Answering system's different implementations☆10Updated 7 years ago
- RF + GBM + ARIMA/NN Hybrid ensemble for predicting 6-month returns for the 9 sector ETFs plus IYZ☆23Updated 10 years ago
- Code to munge data between Kaggle .tsv Rotten Tomatoes Sentiment Analysis data set and Vowpal Wabbit☆24Updated 10 years ago
- The notes and slides from my PyCon Ireland 2016 PyData talk an introduction to gradient boosting☆18Updated 8 years ago
- Introduction to structured prediction with Python and pystruct☆18Updated 6 years ago
- Capturing Structure Implicitly from Noisy Time-Series having Limited Data☆0Updated 6 years ago
- Easily visualize embedding on tensorboard with thumbnail images and labels.☆27Updated 6 years ago
- Code for KDD 2014☆16Updated 9 years ago
- Various notebooks and tutorials on subjects of interest.☆36Updated 4 years ago
- ☆10Updated 9 years ago
- Code for the "Burn CPU, burn" competition at Kaggle. Uses Extreme Learning Machines and hyperopt.☆33Updated 10 years ago
- Starter kit for getting started in the NIPS 2017 Criteo Ad Placement Challenge☆19Updated 7 years ago
- A comparison of various Robust PCA implementations☆14Updated 8 years ago