Displaying 1 to 11 from 11 results

Deep-Learning-Boot-Camp - A community run, 5-day PyTorch Deep Learning Bootcamp

  •    Jupyter

Tel-Aviv Deep Learning Bootcamp is an intensive (and free!) 5-day program intended to teach you all about deep learning. It is nonprofit focused on advancing data science education and fostering entrepreneurship. The Bootcamp is a prominent venue for graduate students, researchers, and data science professionals. It offers a chance to study the essential and innovative aspects of deep learning. Participation is via a donation to the A.L.S ASSOCIATION for promoting research of the Amyotrophic Lateral Sclerosis (ALS) disease.

kaggle-airbnb-recruiting-new-user-bookings - 2nd Place Solution in Kaggle Airbnb New User Bookings competition

  •    R

2nd place solution for Airbnb New User Bookings Competition. Note: This code should be differ from my submitted solution(Public:0.88209/Private:0.88682) because of the seed settings. if you select a model of more than 5 fold-CV 0.833600, you can get about 0.88682(Private).

Apartment-Interest-Prediction - Predict people interest in renting specific NYC apartments

  •    Jupyter

Predict people interest in renting specific apartments. The challenge combines structured data, geolocalization, time data, free text and images. This solution features Gradient Boosted Trees (XGBoost and LightGBM) and does not use stacking, due to lack of time.

open-solution-ship-detection - Open solution to the Airbus Ship Detection Challenge

  •    Python

This is an open solution to the Airbus Ship Detection Challenge. In this open source solution you will find references to the neptune.ml. It is free platform for community Users, which we use daily to keep track of our experiments. Please note that using neptune.ml is not necessary to proceed with this solution. You may run it as plain Python script 🐍.

open-solution-toxic-comments - Open solution to the Toxic Comment Classification Challenge

  •    Python

Here, at Neptune we enjoy participating in the Kaggle competitions. Toxic Comment Classification Challenge is especially interesting because it touches important issue of online harassment. You need to be registered to neptune.ml to be able to use our predictions for your ensemble models.

xgboost-node - Run XGBoost model and make predictions in Node.js

  •    Cuda

XGBoost-Node is a Node.js interface of XGBoost. XGBoost is a library from DMLC. It is designed and optimized for boosted trees. The underlying algorithm of XGBoost is an extension of the classic gbm algorithm. With multi-threads and regularization, XGBoost is able to utilize more computational power and get a more accurate prediction. The package is made to run existing XGBoost model with Node.js easily.