What is TinyML TinyML is that segment of machine learning which can be used to develop low power-consuming devices that can run on both machine learning and deep learning models. TinyML has a significant role in combining the machine learning community with IoT technology. By using it, we can directly deploy models and gain insights […]
TinyML and it’s Implications Read More »
Computer Vision (CV) is the field of AI which helps computers replicate the human visual system and enables computers to identify images, videos like we do. One such vital application of computer vision is facial recognition, digital image processing. There are many industry applications as well. Computer vision algorithms are heavily utilized to understand customer
Computer Vision – A beginners approach Read More »
Among the many applications of machine learning (ML) that has been a success, self-driven car is one of them. A self-driven car, a.k.a. autonomous car or driver-less car is a vehicle which can sense its own environment and drive without any human intervention. Since the last few years, tech companies have been pairing up with
Self-driven Car Industry – a sneak peek Read More »
The highest number of people with diabetes is in China and India. India ranks 76th with around 9% prevalence. 46% of people around the world with diabetes go undiagnosed. By 2040, this figure is expected to rise to 642 million worldwide. Many people with diabetes are diagnosed late and hence develop Type II diabetes. Predicting
Use of Artificial Intelligence in Diabetes Prevention Read More »
Predictive Analytics is a branch of advanced analytics which is very useful for medical diagnosis in the healthcare industry. Historical data of former patient’s symptoms is applied to assess new patients and reduce misdiagnosis. In healthcare segment, it can cater to patient diagnosis by determining patients who are at risk of developing conditions for example
Using Predictive Analytics for Patient Diagnosis Read More »
KNIME is an open-source, modular framework (or platform) for graphically building and executing workflows and data analysis pipelines from predefined components (called “nodes”). As the heading suggests, it is a platform to automate and integrate different components for machine learning and data mining through its modular data pipelining concept. KNIME contains a collection of nodes.
KNIME – an Ideal Platform for Data Analytics and ML Read More »
Machine Learning (ML) is a subset of the wider field of artificial intelligence. It is the area of technology where computers are fed large amounts of data and by applying algorithms, computers find patterns and make accurate predictions based on that data without any human intervention. Present Scenario for AI and Machine Learning in Small Business
Machine Learning in Small Business Read More »
XGboost is short for eXtreme Gradient Boosting package. Before diving deep into XGBoost, let us first understand Gradient Boosting and just Boosting. Boosting is a machine learning ensemble meta-algorithm for primarily reducing bias and variance in supervised learning and a family of machine learning algorithms that convert weak learners to strong ones. Algorithms that achieve
Boosting in Machine Learning using XGBoost Read More »
There is a big difference between a traditional algorithm and a machine learning algorithm (ML). Traditional algorithms are designed for problems which we already know how to solve and so we explicitly program the computer to solve them. In contrast, machine learning algorithms deal with problems without clear-cut steps towards a solution. In machine learning,
A Beginners Approach to Machine Learning Algorithms Read More »