Why I Chose Python for Machine Learning?

I am going to start learning machine learning, and the first question that arose in my mind is this: since it is a part of computer science, there must be some programming language used. We all know that the language used for machine learning or any kind of data science is none other than Python. But why Python and not Java, C, or any other languages?

Since my school days, I have been using Java. I wondered why we were not using Java or C (which I had learned in the first semester of my Bachelor’s degree).

After browsing online, I found several reasons.

Python is an amazing choice for machine learning, and it’s easy to see why! With user-friendly libraries like NumPy and Pandas, it makes data analysis and building machine learning models a breeze. On the other hand, Java's machine learning tools aren’t as well-known or as easy to work with.

One of the fantastic things about Python is how simple and intuitive it is. You can accomplish more with less code, which is incredibly helpful when you're trying out new ideas. Java tends to require a lot more lines of code, which can slow things down, especially when you want to experiment quickly. That flexibility is what makes Python the go-to choice in machine learning research!

Plus, Python has some cool interactive tools, like Jupyter Notebooks, that let you write code and see the results instantly. This is super useful when you're learning or experimenting. Unfortunately, Java doesn’t have anything quite like that, which can make trying out new machine-learning concepts a bit trickier.

Let’s talk about communities! Python has a vibrant and supportive community focused on machine learning and data science. This means it’s easy to find help, tutorials, and code examples. In contrast, Java's community leans more towards web development and large software systems, so there’s not as much support for machine learning.

Now, let's look at why C isn't typically used for machine learning when compared to Python. C is a lower-level language, which means it requires more code for even simple tasks. It also involves manual memory management, which can be tricky and lead to mistakes. Unlike Python, C doesn’t come with built-in libraries to make machine learning easier.

Like Java, C can be slow for development and experimentation, and it lacks interactive tools and a community focused on machine learning. Plus, machine learning often involves high-level math and matrix operations, which Python handles brilliantly with libraries like NumPy. In C, you’d have to implement those algorithms manually, which can be a bit of a slog!

That said, it’s interesting to note that some powerful libraries like TensorFlow and PyTorch are actually written in C or C++ to boost performance. So while C might not be the first choice for machine learning, it definitely plays a key role in making those powerful algorithms run efficiently.

Having learned all this about why Python is such a fantastic option for machine learning, I’m really excited to start learning it myself! If you have any other thoughts or points you want to add, feel free to share! I'm more than happy to read and discuss them. I can’t wait to share my journey with you all in my next blog. Stay tuned for what I discover!