In recent years, the integration of machine learning (ML) techniques with material science research has catalyzed innovation, revolutionizing traditional approaches to material discovery, characterization, and optimization. This article explores the diverse applications of ML in material science, highlighting its transformative impact on various research domains. Areas in Material Science where Machine Learning is Used Prediction …
Introduction TinyML is the field which involves deployment of machine learning models into resource constrained devices such as micro-controllers. Such devices called edge devices often have few Kilobytes of RAM and flash memory but consumes power in milli-watts range. This feature makes the technology an ideal choice for remote sensing applications, weather stations, tiny gadgets …
In many situations, it is desirable to start certain programs or softwares automatically while a computer boots up. In this article we will see few ways we can achieve this objective using some settings in Linux systems. The Bashrc method This is one of the easiest methods to load a program or script while a …
A lot of useful applications of machine learning use deep learning as the backbone technology. Deep learning is the key reason behind the second wave of AI we see these days. A deep learning engineer solving various problems might be using various deep learning libraries on a day to day basis. Tensorflow and Keras are …
In this article I will show you how to create common python plots using Python programming language and dummy data. People from Science, Technology, Engineering and Medicine (STEM) fields often have to deal with scientific charts and graphs. They might use it to communicate their findings as well as learn the latest findings from their …
The use of computational tools for data preprocessing and analysis is daily activity for any bioinformatician. Having a interdisciplinary field, a plethora of tools exist in the domain, written by developers from various fields and languages. Many times there can be multiple candidate tools exists to accomplish any given task. Often it is the decision …
If you have some raw data and want to convert in into meaningful insight, feature engineering in machine learning is one of the best tools to help you. Imagine a real-life situation where you want to know how frequently a customer order food from your restaurant in order to offer best customer service. In such …
The Jupyter Notebook is best suited for doing as well as documenting empirical research. It can contain text, code images, videos, interactive content, and also nicely typesetting equations. This makes anyone doing simulations or empirical research prototype their work and share it with their colleagues. The same Jupyter notebook can be used to visualize protein …
Visualizing Protein Structures in Jupyter Notebook Read More »
Graphical User Interface (GUI) has been useful and easy to use for all types of computer users. We all use it every day to get things done. However, the computing history has the provision to do command-line instructions also to do the same things. Linux terminal is one such command line interface. Let us take …
In STEM fields it is often required to communicate ideas using graphs or infographics. Many times the dimensionality of data will be higher and require clever hacks to represent so that the reader gets the idea quickly. There have been systematic studies on how to do data visualization effectively. For data scientists or machine learning …
Python Matplotlib Tip: Overlapping Curves and Multiple Axes Read More »