After six months of learning Machine Learning, I have encountered issues many beginners face. Here is some advice on how to tackle them effectively.
1. Learning Python
I’ve noticed many of my friends weren’t initially good at Python but started learning Artificial Intelligence. Python is essential for Machine Learning, and without it, implementation becomes challenging. It’s a good idea to understand the basics of Python, including loops, conditional statements, functions, data types, and classes, for a better grasp. Learning these basics typically takes about 10-15 days. Libraries like NumPy, Pandas, and scikit-learn can be learned along the way.
2. Learning From Different Sources
Another common mistake people make is referring to different sites and notes during the early days of learning ML. What i recommend is to either take a paid course over the Internet or stick to a single source throughout. This helps in maintaining continuity in the subjects.
3. Lack of Practice
Mostly, the people try to rush and go through the theory completely. AI is not a small subject to be completed in a few weeks. It takes months to complete it. Also with the current emerging Gen AI, it became more necessary to stay updated. So, if you want to remember the vast amount of data, practice is the key. So, consider using 60% of your time for practice and remaining time to learn new stuff. There are many platforms like kaggle to practice and improve your skills.
4. Better Community
Creating a better community among your friends will help learn Machine Learning faster. Form study groups, share resources, and participate in hackathons. A strong community can be invaluable for discussing ideas, solving doubts, and collaborating on projects.
These activities not only boost your skills but also keep you motivated. Platforms like Discord, Reddit, and LinkedIn are great for connecting with like-minded individuals.
5. Selecting a Path after Machine Learning
Learning only Machine Learning may not be sufficient for a successful career in the current scenario. From the other extensions like computer vision, natural language processing , Gen AI, etc, specializing in one based on your interests and building your career over that will be helpful.
Artificial Intelligence is a fascinating journey that requires patience, practice, and focus. Start small, stay consistent, and don’t hesitate to reach out to the community for support. Remember, every expert was once a beginner!
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