Learning Project.

Applied AI Course assignment work.

Objective :

The aim of this project was to learn how to do data analysis and apply techniques like Feature Engineering, Training ML Models etc.

Outcomes :

1. Learnt how to do Sentiment analysis.
2. Learnt how to apply concepts Like Bag of Words, Tfidf and Wor2Vec.
3. Learnt how to do Text Preprocessing.
4. Learnt various Supervised Learning Techniques like (Logstics Regression, SVM's, Decision Trees, GBDT's, RF's, AdaBoost etc)
5. Learnt how to perform Dimensionality Reduction.
6. Learnt how to handle large dimensional Data.
7. Learnt about the curse of dimensionality problem.
8. Performed Clustering by removing the labels from the dataset.
9. Generated Cooccurance Matrix and Applied Matrix Factorization.
10. Finally Learnt what works best in what situation. (Like Logistics Regression works well when dimensionality is high).

Conclusions :

An Enlightening Introduction to Machine Learning providing skills to work on future projects.