Today there are a huge number of libraries for machine and deep learning. We are going to describe only the most popular and necessary libraries that cover all the basic needs to start working with ML and DL. So, here is the list of ML and DL best libraries.
- The R programming language was created for solving statistical problems and is very popular among data analysts.
- Python is a general-purpose language and can be successfully applied to various tasks.
- Jupyter Notebook is a simple and powerful data analysis tool.
- Scikit-learn is one of the most popular ML libraries today.
- Pandas is a powerful tool that allows you to quickly analyze, modify and prepare data for other ML and DL libraries.
- The main functionality of NumPy is to support multidimensional data arrays and fast linear algebra algorithms.
- Matplotlib is a standard tool in the data engineer set.
- PyTorch is the second most popular DL library after Tensorflow, which was created on Facebook.
Here you can find a more detailed description of each of them.
If you are considering which DL library to choose, the best answer would be to find an online course that you like, so that the course will make the choice for you in a result!
And don’t miss a chance to participate in AI & Big Data Day 2019 conference and to know about the latest developments in the field of artificial intelligence and Big Data processing.
p.s. No, robots will not conquer the world and kill all the people.