ML Workflow & Taxi Trip Prediction | Machine Learning Practices | Session - 4

ML Workflow & Taxi Trip Prediction | Machine Learning Practices | Session - 4
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In this session, we've covered:- Complete ML Workflow
- What are Features (X), Target Label (y)
- Linear Regression
- EDA
- Feature Engineering
- Ordinal Encoding- Predicting Taxi Trip duration
Kaggle notebook 🔼 (Make sure to upvote it)
www.kaggle.com/param302/mlp-s...
Dataset used:
www.kaggle.com/datasets/param...
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Chapters:
00:00 Overview & Questions
04:45 Jupyter Notebooks Overview
22:54 ML Workflow
31:13 Data, Features & Target label
36:03 Linear Regression
45:42 Importing libraries
46:02 Importing Data
48:34 EDA
1:11:00 Feature Engineering
1:29:27 Feature Transformation - Ordinal Encoding
1:48:48 Modeling - Linear Regression
1:52:59 Predicting Test data
2:00:55 Submitting Predictions
2:04:04 Summary
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[@Adaa512]

Nice session 🙌

[@Param3021]

Thanks!

[@praulayar4805]

plz make videos on matplotlib and seaborn , visualization lib , maybe even plotly and how to show graphs and charts in MLP projects

[@Param3021]

Oky, I will do polls in groups, if got good amount of votes, will do a session.
Also now in each and every session we will do a lot of visualization.