Are you trying to figure out how much Python is needed for machine learning and want to become a good ML programmer? Don’t worry, we have got you covered! This article shall cover all the queries you have related to Python and its relation with ML. Not only will answer your queries but it will give you a better idea of how to go about things. So, let’s dive into it.
How much Python is needed for Machine Learning?
You simply need to be familiar with the fundamentals of Python to use it for machine learning, like printing to the screen, obtaining user input, conditional statements, looping statements, object-oriented programming, etc. These principles are essential to be able to write your code and comprehend the code written by others. Let’s explore some common questions related to machine learning and Python.
I. What are the prerequisites for learning Machine Learning?
You need to have at least a basic idea and understanding of variables, histograms, graphs of functions, linear equations, and statistical means. Ideally, you need to learn Python before you begin with ML. Good programming skills are essential.
Additionally, some mathematical skills will also help with machine learning. You may need to know Algebra, Linear Algebra, Trigonometry, Stats, Calculus (derivatives, Fourier series, gradients, and slopes, etc).
II. What Python libraries are needed for Machine Learning?
Here is a list of important Python libraries necessary for Machine Learning:
- Pandas
- NumPy
- TensorFlow
- Scikit-learn
- Keras
- PyTorch
- Matplotlib
- Seaborn
- Theano
- SciPy
III. Can I do Machine Learning with any other programming language?
Yes, you can do it with other programming languages too. Although Python is the best and most suitable for this job, you can still use any other programming language. Here are all the languages you can try to code in for ML:
- R Programming
- TypeScript
- JavaScript
- Java
- Shell
- Lisp
- Scala
- C
- C++
- GO
- Julia
IV. Are Artificial Intelligence and Machine Learning the same?
No, artificial intelligence and machine learning are not the same. In reality, machine learning is a subset of machine learning. It comes under ML. They are closely related but are not the same.
V. Should I learn Artificial Intelligence before learning Machine Learning?
It is not necessary to learn artificial intelligence first but ideally, it seems like a good idea to begin with it first. We know that machine learning is a subset of artificial learning, so you can even begin with machine learning directly.
VI. Where is Machine Learning used? What are its applications in real life?
You will see machine learning’s applications in the following fields:
- Instagram uses it. Many social media platforms use it.
- It is used by Google for traffic detection, transportation, and commuting. It is used in Google Translate as well.
- The most prominent use of machine learning is seen in self-driving cars like Tesla.
- Streaming videos online also requires machine learning. Famous sites like Twitch and Netflix use it.
- Machine learning is also used in virtual personal assistants like Siri, OK Google, Cortana, and more. It is used in speech recognition, text-to-speech conversion, and NLP or natural language processing.
Conclusion
To sum this up, you need to have a good amount of Python knowledge before you begin with ML. You should know the looping statements, print statements, expressions, conditions, and more. ML falls under AI and ML is used in a lot of fields. It is used by Amazon, Google, Apple, etc. So, get on the journey to learn Python and machine learning and develop awesome projects! ML will always be in trend and will only progress in the future.
Happy Learning!
Also Read: Coding vs. Programming vs. Scripting | Know the Difference
