πŸš€ Starting Your Journey as an AI/ML Engineer: My Roadmap and Insights



This content originally appeared on DEV Community and was authored by Arpit Kadam

Hey dev community! πŸ‘‹

I’m Arpit Kadam, a third-year AIML student passionate about all things artificial intelligence and machine learning. Having worked on multiple projects like stock market forecasting, salary prediction, and car price estimation, I’ve learned quite a bit along the way. Today, I want to share my experience and the roadmap that has helped me grow as an AI/ML engineer, hoping it will serve as a useful guide for anyone starting out!

Start with the Basics: Build a Strong Foundation
Before diving into the complex world of AI and ML, it’s crucial to have a solid understanding of programming fundamentals, mathematics, and statistics.

Programming Skills: Python is your best friend! It’s widely used in AI/ML projects. Learn the basics of Python, such as data structures, OOP, and libraries like NumPy and Pandas.

Mathematics: AI and ML are all about understanding patterns in data. Topics like linear algebra, calculus, and probability play an essential role in building efficient models.

Statistics: ML revolves around data, and understanding data requires knowledge of statistics. Concepts like mean, variance, distributions, and hypothesis testing will help a lot.

Learn Core Machine Learning Concepts
Once you’ve got the basics down, it’s time to get hands-on with machine learning algorithms.

Supervised Learning: Understand classification and regression algorithms. My initial ML project involved building a car price prediction model using Linear Regressionβ€”a great way to start!

Unsupervised Learning: Algorithms like K-Means clustering and Principal Component Analysis (PCA) help you with tasks where labels are not available.

Deep Learning: This is where the magic happens! Dive into neural networks using frameworks like TensorFlow or PyTorch. I’ve found them incredibly useful for complex tasks.

Real-World Projects: The Key to Mastery
Theory is important, but nothing beats learning from real-world projects. I started working on projects like:

Stock Forecast App: Used Prophet and yfinance to predict stock prices, and hosted it using Streamlitβ€”a great way to understand the end-to-end ML pipeline.

Salary Prediction Model: Predicted software developer salaries using various regression models and explored the impact of different features like experience and location.

And many more…..

Working on diverse projects teaches you how to collect, clean, and preprocess data, train models, and evaluate their performance.

Stay Curious: Explore Advanced Topics
I’m constantly trying to enhance my knowledge, not just to shine in projects but also to contribute more effectively to the field. Here are some areas I’m currently exploring:

Natural Language Processing (NLP): With the rise of chatbots and virtual assistants, NLP is becoming more critical than ever. I’ve been experimenting with transformers and models like BERT.

Computer Vision: Projects like image classification and object detection are fascinating. Tools like OpenCV and deep learning models like CNNs are great for such tasks.

Reinforcement Learning: Though still an emerging field, RL is proving highly effective in areas like robotics and game theory. I plan to explore this more deeply soon!

Share and Collaborate
Finally, I can’t stress this enough: Document your work and share it! Whether through blog posts, GitHub repositories, or presentations, sharing not only helps you retain knowledge but also opens doors to networking and collaboration. I’ve uploaded my work to GitHub and even started a YouTube channel to explain hard technical topics.

πŸ“« Let’s Connect!
If you’d like to discuss AI/ML, collaborate on a project, or just want to chat about tech, feel free to reach out to me! Here’s where you can find me:

Email: arpitkadam922@gmail.com
GitHub:

ArpitKadam (Arpit Kadam) Β· GitHub

ArpitKadam has 8 repositories available. Follow their code on GitHub.

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Phone: +91-8767375722

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I’m always open to learning, connecting with like-minded individuals, and collaborating on interesting projects! Feel free to ping me on any of the platforms above. 😊


This content originally appeared on DEV Community and was authored by Arpit Kadam