Data Science & Machine Learning

To start with Machine Learning:

1. Learn Python
2. Practice using Google Colab

Take these free courses:

https://t.iss.one/datasciencefun/290

If you need a bit more time before diving deeper, finish the Kaggle tutorials.

At this point, you are ready to finish your first project: The Titanic Challenge on Kaggle.

If Math is not your strong suit, don't worry. I don't recommend you spend too much time learning Math before writing code. Instead, learn the concepts on-demand: Find what you need when needed.

From here, take the Machine Learning specialization in Coursera. It's more advanced, and it will stretch you out a bit.

The top universities worldwide have published their Machine Learning and Deep Learning classes online. Here are some of them:

https://t.iss.one/datasciencefree/259

Many different books will help you. The attached image will give you an idea of my favorite ones.

Finally, keep these three ideas in mind:

1. Start by working on solved problems so you can find help whenever you get stuck.
2. ChatGPT will help you make progress. Use it to summarize complex concepts and generate questions you can answer to practice.
3. Find a community on LinkedIn or 𝕏 and share your work. Ask questions, and help others.

During this time, you'll deal with a lot. Sometimes, you will feel it's impossible to keep up with everything happening, and you'll be right.

Here is the good news:

Most people understand a tiny fraction of the world of Machine Learning. You don't need more to build a fantastic career in space.

Focus on finding your path, and Write. More. Code.

That's how you win.✌️✌️

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Data Science & Machine Learning

🚀 Roadmap to Become a Machine Learning Engineer 💻

📂 Programming Basics
∟📂 Master Python & OOP
∟📂 Learn Data Structures & Algorithms
∟📂 Master Git & Version Control

📂 Mathematics for ML
∟📂 Linear Algebra & Calculus
∟📂 Probability & Statistics
∟📂 Optimization Techniques

📂 Data Handling & Processing
∟📂 Work with Pandas & NumPy
∟📂 Data Cleaning & Preprocessing
∟📂 Feature Engineering & Selection

📂 Machine Learning Fundamentals
∟📂 Understand Supervised & Unsupervised Learning
∟📂 Master Scikit-Learn & ML Algorithms
∟📂 Model Training, Evaluation & Tuning

📂 Deep Learning & Neural Networks
∟📂 Learn TensorFlow & PyTorch
∟📂 Build & Train Neural Networks
∟📂 Master CNNs, RNNs & Transformers

📂 ML System Deployment
∟📂 Learn Model Deployment (Flask, FastAPI)
∟📂 Work with MLOps & Cloud Platforms
∟📂 Deploy Models to Production

📂 Projects & Real-World Applications
∟📂 Build End-to-End ML Projects
∟📂 Work on Open-Source Contributions
∟📂 Showcase on GitHub & Kaggle

📂 Interview Preparation & Job Hunting
∟📂 Solve ML Coding Challenges
∟📂 Learn System Design for ML
∟📂 Network & Apply for Jobs

✅️ Get Hired

React "❤️" for More 👨‍💻

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3.21K views10:50

Data Science & Machine Learning