๐Œ๐š๐œ๐ก๐ข๐ง๐ž ๐‹๐ž๐š๐ซ๐ง๐ข๐ง๐  ๐‘๐จ๐š๐๐ฆ๐š๐ฉ โ€“ ๐…๐ซ๐จ๐ฆ ๐™๐ž๐ซ๐จ ๐ญ๐จ ๐„๐ฑ๐ฉ๐ž๐ซ๐ญ

โ†’ ๐’๐ญ๐ž๐ฉ ๐Ÿ: Build Your Foundations

โ˜‘Mathematics

Linear Algebra โ†’ Matrices, Vectors, Eigenvalues

Probability โ†’ Bayesโ€™ Theorem, Distributions

Calculus โ†’ Gradients, Optimization

โ˜‘ Programming

Python โ†’ Master libraries like NumPy, Pandas, Matplotlib

Learn OOP concepts for better model building

โ†’ ๐’๐ญ๐ž๐ฉ ๐Ÿ: Data Handling

โ˜‘ Work with real datasets โ†’ Cleaning, preprocessing, and visualization

โ˜‘ Get hands-on with data analysis tools โ†’ Pandas, Seaborn, SQL

โ†’ ๐’๐ญ๐ž๐ฉ ๐Ÿ‘: Core Machine Learning

โ˜‘ Understand Supervised Learning

Regression (Linear, Logistic)

Classification (SVM, Decision Trees, etc.)

โ˜‘ Dive into Unsupervised Learning

Clustering โ†’ K-means, DBSCAN

Dimensionality Reduction โ†’ PCA

โ†’ ๐’๐ญ๐ž๐ฉ ๐Ÿ’: Advanced Topics

โ˜‘ Neural Networks

Learn TensorFlow/PyTorch for building deep learning models

Study architectures like CNNs, RNNs, Transformers

โ˜‘ Model Deployment

Understand MLOps โ†’ Model serving, monitoring, and pipelines

โ†’ ๐’๐ญ๐ž๐ฉ ๐Ÿ“: Practical Projects

โ˜‘ Work on real-world problems โ†’ Predictive analysis, recommendation systems, NLP applications

โ˜‘ Build a portfolio to showcase your skills โ†’ GitHub, personal website

๐“๐ข๐ฉ: Focus on learning by doing, not just theory. Apply concepts as you learn!

Credits Arif Alam

amrelarabi

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