AdrishMaity

Kaggle Competitions

• Titanic: Machine Learning from Disaster
• House Prices: Advanced Regression Techniques
• Digit Recognizer
• Porto Seguro’s Safe Driver Prediction
• New York City Taxi Trip Duration
• Spaceship Titanic
• Petals to the Metal - Flower Classification on TPU
• Natural Language Processing with Disaster Tweets

AdrishMaity

Should I need to start over, I would pursue this path to first grasp the fundamentals of Python for Data Science, Machine Learning and understand the core concepts:

• Learn basics of Python [https://www.youtube.com/watch?v=rfscVS0vtbw&ab_channel=freeCodeCamp.org]
• How to use Python for Data Science (basics) [https://www.freecodecamp.org/news/learn-pandas-for-data-science/]
• Mathematics for ML [https://www.youtube.com/watch?v=0z6AhrOSrRs&ab_channel=MyLesson]
• Data Analysis with SQL [https://www.udemy.com/course/the-complete-sql-masterclass-for-data-analytics/]
• Data Analysis and Visualisation in Python [https://youtu.be/GPVsHOlRBBI?si=ZXbHFUaCHELBSIy4]
• Statistics Essentials (inferential Statistics mostly) with Hypothesis Testing
  • [Book: https://www.oreilly.com/library/view/practical-statistics-for/9781491952955/]
• https://www.khanacademy.org/math/statistics-probability

AdrishMaity

Make sure git is tracking your project.

1. Using your terminal/command line, get inside the folder where your project files are kept: cd /path/to/my/codebase.

You cannot do this simply by opening the folder normally, you must do this with the command line/terminal.

Do you need a refresher on using your command line/terminal? I've compiled my favorite resources here.

2. Check if git is already initialized: git status