kunaalnaik / yt_kaggle_mastery

Kaggle is a place where you can improve your Data Science Skills. Follow this repo as a guide to help you progress in Kaggle.

Kaggle Mastery

Being in the Data Science field its important that you keep practising your Problem Solving skills. Kaggle provides a platform to atleast practise the Feature Engineering & Moddelling aspect. Also, Kaggle provides a glimpse into Real World problems. To participate in Kaggle requires dedicated effort and focus to move up the progression and rank in any of the categories. Few months back I challenged myself to paticipate in Kaggle and move up ranks. In this Repository I plan to record all that I discover along the way.

Start by Becoming a Contributor on Kaggle Video Link

Important Links:

• Article on Using TPU on Kaggle | Sample Solution

1/ Kaggle Datasets Uploaded

• Data Science YouTube Channel Collection to Learn
• Retail Data Customer Summary (Learn Pandas Basics)

2/ Kernels for Learning

Pandas Basics (Use Working Code if you want write codes yourself)

• Completed Code: Introduction to Pandas Dataframes
• Working Code: Introduction to Pandas Dataframes)

Competition Solutions for Learning

Titanic Solution | Video Tutorials

• Titanic Basic Solution with Logistic Regression
• Titanic Solution : Random Forest
• Titanic Solution with basic H2O
• Titanic Solution with Auto H2O

Getting Started Machine Learning Codes [Basic]

• P1 : sklearn Logistic Regression | Video
• P2 : Logistic Regression - hyperparameter tuning | Video
• P1 : sklearn SVM Model | Video

Getting Started Machine Learning Codes [Intermediate]

• P1: Basic sklearn Randon Forest model|Video
• P2: sklearn Randon Forest parameter tuning

Getting Started Machine Learning Codes [Intermediate]

• P1 : Develop your first XGBoost model on Python | Video
• P2: XGBoost - Train, Test and Predict
• P3: XGBoost Hyperparameter Tuning Python - v1

Follow me on Kaggle for Kaggle Adventure!

• My Kaggle Profile Link