Alternatives and similar repositories for jh-kaggle-util

Users that are interested in jh-kaggle-util are comparing it to the libraries listed below

• abhishekkrthakur / mlframework
  ☆203Updated last year
• tklouie / PyData_LA_2018
  Added repo for PyData LA 2018 tutorial
  ☆88Updated 6 years ago
• vopani / fortyone
  Machine Learning begins with Human Learning
  ☆108Updated 4 years ago
• legolas140 / competitive-data-science-1
  How to Win a Data Science Competition: Learn from Top Kagglers
  ☆174Updated 7 years ago
• mervynlee94 / Advance-Machine-Learning
  ☆85Updated 7 years ago
• dipanjanS / deep_transfer_learning_nlp_dhs2019
  Contains the code and deck for the presentation on Applying Deep Transfer Learning for NLP in Analytics Vidhya's DataHack Summit 2019
  ☆82Updated 5 years ago
• rajat5ranjan / AV-LTFS-Data-Science-FinHack-ML-Hackathon
  L&T Financial Services & Analytics Vidhya presents ‘DataScience FinHack’ organised by Analytics Vidhya
  ☆55Updated 6 years ago
• bhavsarpratik / data-science-interview-assignments
  Real data science interview assignments
  ☆94Updated 5 years ago
• trainindata / testing-and-monitoring-ml-deployments
  Example project for the course "Testing & Monitoring Machine Learning Model Deployments"
  ☆136Updated last year
• dipanjanS / tensorflow2-crash-course
  A quick crash course in understanding the essentials of TensorFlow 2 and the integrated Keras API
  ☆227Updated 4 years ago
• parulnith / What-I-learnt-by-interviewing-numerous-Kaggle-Grandmasters
  ☆38Updated 4 years ago
• SudalaiRajkumar / DHS2019_HackSession_NLP
  Codes used for the hack session in DHS 2019
  ☆53Updated 5 years ago
• knathanieltucker / deep-learning-building-blocks
  ☆33Updated 2 years ago
• klemag / pydata_nyc2018-intro-to-model-interpretability
  Notebook and slides for my talk at Pydata NYC 2018
  ☆88Updated last year
• kunalj101 / amExpert_ML_Hackathon_2019_Winners_Soultions
  ☆23Updated 2 years ago
• sahil711 / AV
  Contains solutions to AV competitions
  ☆21Updated 2 years ago
• davidyakobovitch / data_science_resources
  📊 Data Science Resources, Data Science Standards & Machine Learning Pipelines
  ☆161Updated 3 years ago
• harnav / pydata-docker-tutorial
  Tutorial given at PyData LA 2018
  ☆97Updated last year
• mrdbourke / cs329s-ml-deployment-tutorial
  Code and files to go along with CS329s machine learning model deployment tutorial.
  ☆611Updated 2 years ago
• lmassaron / kaggledays-2019-gbdt
  Kaggle Days Paris - Competitive GBDT Specification and Optimization Workshop
  ☆92Updated 2 years ago
• aayushmnit / cookbook
  A repository of machine learning codes written for re-usability
  ☆143Updated 5 years ago
• vopani / datatableton
  100 exercises to learn Python Datatable
  ☆270Updated 3 years ago
• jiadaizhao / Advanced-Machine-Learning-Specialization
  Advanced Machine Learning Specialization on Coursera
  ☆221Updated 6 years ago
• shravankoninti / AV
  Analytics Vidhya Hackathons and Others
  ☆26Updated 5 years ago
• amueller / aml
  Applied Machine Learning with Python
  ☆80Updated last year
• bgweber / DS_Production
  ☆155Updated 5 years ago
• hse-aml / competitive-data-science
  Materials for "How to Win a Data Science Competition: Learn from Top Kagglers" course
  ☆660Updated 5 years ago
• Sangarshanan / time-series-forecasting
  Understanding time series forecasting
  ☆65Updated 5 years ago
• tanujjain / deploy-ml-model
  Deploying a simple machine learning model to an AWS ec2 instance using flask and docker.
  ☆81Updated 6 years ago
• aprilypchen / depy2016
  ☆110Updated 9 years ago