Libraries You Should Explore for Data Science & Machine Learning in 2023
Popular Python libraries that you can explore
Python has been gaining a lot of traction in recent years and for good reasons. You can use Python to create web applications using Python web frameworks, develop/create games, create graphical user interface applications and the list goes on. In today’s post, I will be talking about popular Python libraries that you can explore today to learn data science and machine learning. Without further ado, here are the popular machine learning and data science libraries in Python. It’s important to note that every library listed is open-source and free to use.
Data Science Libraries:
NumPy: NumPy is a SciPy stack and Python library that provides an abundance of useful operations on n-arrays and matrices in Python. It helps to create multi-dimensional arrays. It is the fundamental package for scientific computation with Python.
Pandas: Pandas is a Python library that is designed to work with labelled and relational data. Pandas is designed for quick and easy data manipulation, aggregation, and visualization.
Matplotlib: Matplotlib is a SciPy stack core package that is designed for generating simple and powerful visualizations with ease. With the help of other Python libraries such as Numpy and Pandas, it proves to be a recognizable competitor against other scientific tool like MatLab. With some effort and work, you can create visualizations of Line plots, Scatter plots, Pie charts, Histograms, Bar charts, etc.
Machine Learning Libraries:
TensorFlow: Tensorflow is an open-sourced Python library developed by Google. It was designed by Google to meet its high-demand requirements for developing/ training neural networks. The key feature of TensorFlow is its multi-layered nodes system that enables quick training of artificial neural networks on large datasets. This powers Google’s voice recognition and object identification from pictures.
PyTorch: PyTorch is a free, open-source machine learning library, used for applications such as natural language processing and computer vision developed by Facebook’s Artificial Intelligence Lab. Multiple deep-learning software has been built including Tesla’s autopilot system.
Keras: Keras is a software library that provides a Python interface for artificial intelligence neural networks. It also acts as an interface for the TensorFlow library. Keras contains numerous implementations of commonly used building blocks for neural networks such as optimizers, activation functions, loss functions, etc.
SciKit-Learn: SciKit-Learn is an open-source software library built on NumPy, SciPy, and Matplotlib, used for efficient data mining and data analysis such as Object/Image Classification, Regression analysis that can be applied to predicting stock market prices, Clustering, etc.
Sign Up for our Newsletter to never miss a time I post an article. You’ll also receive the Ultimate Python Machine Learning Cheat Sheet, The only Machine learning Cheat Sheet you’ll ever receive!!
