Image by Author If you are a machine learning student, researcher, or practitioner, it is crucial for your career growth to have a deep understanding of how each algorithm works and the various techniques to enhance model performance. Nowadays, many individuals tend to focus solely on the code, data, and pre-trained models, often without fully comprehending the machine learning model’s algorithm or architecture. They simply fine-tune the model on a new dataset and adjust hyperparameters to improve performance. However, to […]

Image by Author Reinforcement learning (RL) is a subfield of machine learning where an agent learns to make decisions by interacting with its environment rather than relying solely on pre-existing data. It is an area that blends trial-and-error learning with feedback from actions to improve future performance. In this blog, we will explore 5 free courses that I believe are the best for beginners and professionals interested in entering the exciting field of self-learning robots. 1. Deep RL Course – […]

Image by Author If you’re looking to make a career in data science, you probably know that machine learning is one of the most in-demand skills. Whether you are a beginner looking to break into the field or an experienced professional aiming to level up your expertise, selecting the right machine learning course is super important. So how do you go about choosing the right course that’s a good fit for you? You can consider one of the many in-person […]

Image by Author Deep learning models achieve state-of-the-art performance in several computer vision and natural language processing tasks. If you want to become proficient in deep learning, you should first understand how neural networks work and then proceed to explore the different types and neural network architectures for specific tasks. To help you get started, we’ve compiled a list of free resources—a mix of books, interactive tutorials, and video lectures—that’ll help you learn all about neural networks. The resources are […]

Image by Author Collaborating on a machine learning project is a bit different from collaborating on a traditional software project. In a machine learning project, engineers are working with data, models, and source code. Additionally, they are also sharing features, model experiment results, and pipelines. You can’t just use any code-sharing platform for a machine learning project; you need to select a platform that lets you share code, resolve issues seamlessly, maintain lineage, handle data and models, provide experiment tracking […]