Machine Learning

Machine learning is a sub-branch of Artificial Intelligence, Machine Learning is the process of making a machine learn using an algorithm from your past data and use that knowledge to predict in the future. There are a ton of Machine Learning libraries and algorithms! Choosing the best suitable that suits your data yields you the best results.

At PRONIX our expertise in Machine Learning dive deeps into your data and provides the expert Machine Learning Solutions for your enterprise.

Machine Learning is Broadly divided into three types Supervised Learning, Unsupervised Learning & Reinforcement Learning. Each of these owns their set of algorithms to train a machine learning model, based on the data and requirement best suitable algorithm has to be chosen to build a model and our expertise in Machine Learning domain will do that with perfection.

Supervised Learning

Supervised Learning works on Labeled data, it is the process of making a machine learn or train on the data where the input and output/target are labeled properly. We train the model until it gets the required level of confidence or accuracy to predict future outcomes. Classification & Regression are the classic use cases of Supervised Learning.

Unsupervised Learning

Unsupervised Learning is used to cluster or group data based on a certain set of information. Here there will be no proper output/target variable to predict, based on the context algorithms in unsupervised learning prepare clusters on the data. The outcome of a prediction here is the cluster where that record belongs to. Clustering and Anamoly detection are classic examples of Unsupervised Learning.

Reinforcement Learning

Reinforcement Learning works on the trail & error method. Models in Reinforcement Learning trains themselves continuously using trial & error focusing on maximizing the reward & minimizing the error to come up with the best possible solution. Reinforcement models are iteratively trained to make them more accurate by providing feedback. Driverless cars and Chess games are classic examples of reinforcement learning.

         

We provide expert solutions to our clients using our prowess on the topmost Machine Learning libraries Scikit, Keras, XGBoost, StatsModeles and many more.