Alternatives and similar repositories for ML_Model_for_Predicting_Ships_Crew_Size

Users that are interested in ML_Model_for_Predicting_Ships_Crew_Size are comparing it to the libraries listed below

• MaartenGr / Projects
  Data Science Portfolio
  ☆74Updated 5 years ago
• yug95 / MachineLearning
  Machine learning for beginner(Data Science enthusiast)
  ☆128Updated 9 months ago
• srivatsan88 / model-deployment
  This playlist covers model deployment covered as part of course in YouTube - https://www.youtube.com/playlist?list=PL3N9eeOlCrP5PlN1jwOB3…
  ☆99Updated 5 years ago
• srivatsan88 / YouTubeLI
  Github repo to upload demo files of youtube videos and linkedin
  ☆340Updated 4 years ago
• srivatsan88 / Natural-Language-Processing
  This repository host code of my NLP playlist here - https://www.youtube.com/playlist?list=PL3N9eeOlCrP6zMkHMxFJV4yXIsET5aWlc
  ☆47Updated 5 years ago
• MLWhiz / data_science_blogs
  A repository to keep track of all the code that I end up writing for my blog posts.
  ☆251Updated 3 years ago
• pycaret / deployment-heroku
  Deployment Heroku
  ☆58Updated last year
• Mooseburger1 / Springboard-Data-Science-Immersive
  ☆63Updated 7 years ago
• Jcharis / DataScienceTools
  Useful Data Science and Machine Learning Tools,Libraries and Packages
  ☆237Updated last year
• mrdbourke / airbnb-amenity-detection
  Repo for 42 days project to replicate/improve Airbnb's amenity (object) detection pipeline.
  ☆171Updated last year
• datasciencescoop / Pandas
  Pandas
  ☆104Updated 4 years ago
• srivatsan88 / google_cloud_AI_ML
  This repository contains code to learn AI and ML on Google Cloud Platform
  ☆101Updated 4 years ago
• Pierian-Data / ISLR-python
  An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
  ☆86Updated 9 years ago
• kaburelabs / Datacamp-Courses
  Some of my notebooks of Datacamp courses.
  ☆132Updated 6 years ago
• aiplanethub / Machine_Learning_Bootcamp
  ☆90Updated 5 years ago
• datacamp / Market-Basket-Analysis-in-python-live-training
  Live Training: Market Basket Analysis in Python
  ☆48Updated 5 years ago
• mrdbourke / your-first-kaggle-submission
  How to perform an exploratory data analysis on the Kaggle Titanic dataset and make a submission to the leaderboard.
  ☆224Updated last year
• parulnith / 10-Simple-hacks-to-speed-up-your-Data-Analysis-in-Python
  Some useful Tips and Tricks to speed up the data analysis process in Python.
  ☆61Updated 6 years ago
• PacktWorkshops / The-Deep-Learning-with-Keras-Workshop
  An Interactive Approach to Understanding Deep Learning with Keras
  ☆51Updated 3 weeks ago
• TrainingByPackt / Data-Wrangling-with-Python
  Simplify your ETL processes with these hands-on data sanitation tips, tricks, and best practices
  ☆131Updated 4 years ago
• dipanjanS / nlp_essentials
  Essential and Fundametal aspects of Natural Language Processing with hands-on examples and case-studies
  ☆172Updated 5 years ago
• SThornewillvE / Udacity-DataScience-Nanodegree
  Udacity Data Science Nanodegree Repository. Contains lecture notes, and dummy scripts as well as projects undertaken for the nanodegree.
  ☆31Updated 6 years ago
• piyushpathak03 / Automated-Machine-Learning
  All AutoML Libraries
  ☆108Updated 4 years ago
• SuperJohn / spark-and-python-for-big-data-with-pyspark
  Course on Udemy by Jose Portilla
  ☆98Updated 7 years ago
• suneelpatel / Statistics-for-Data-Science-using-Python
  Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. Learn statistical concepts that a…
  ☆45Updated 6 years ago
• susanli2016 / PyCon-Canada-2019-NLP-Tutorial
  ☆56Updated 6 years ago
• shashi-ai1 / DataScience
  ☆15Updated 4 years ago
• datasciencescoop / Linear-Algebra
  Linear Algebra
  ☆123Updated 2 years ago
• dipanjanS / convolutional_neural_networks_essentials
  Contains presentation deck and notebooks showcasing fundamental concepts and hands-on examples for Convolutional Neural Networks
  ☆46Updated 5 years ago
• suvoooo / Machine_Learning
  Some fundamental machine learning and data-analysis techniques are explained through realistic examples.
  ☆123Updated last year