10 Undiscovered & Open Source Machine Learning Frameworks

Machine Learning (ML) is transforming the way computers work by enabling them to learn and make decisions without being explicitly programmed. Popular frameworks like TensorFlow and PyTorch often dominate the conversation. However, there are numerous lesser-known, open-source ML frameworks that offer innovative features and flexibility for different needs.

In this blog, we will uncover 10 hidden gems in the world of ML frameworks. We’ll start with the basics, explain key concepts, and highlight the unique features of these frameworks. By the end, you will understand why these tools matter and how they are changing the tech landscape.

What is Machine Learning?

Before diving into the frameworks, let’s understand what Machine Learning is.

• Machine Learning (ML): It’s a type of artificial intelligence where machines learn from data to make predictions or decisions without explicit programming.
• Data: Information collected from the world, like numbers, text, or images, used for training ML models.
• Model: A system trained to identify patterns in data and make predictions (e.g., recognizing faces in photos or predicting weather).

Why Use ML Frameworks?