Make better decisions with Google Cloud Document AI

Reading Time: 3 minutes Nearly all business processes today begin, include or end with a document. Most companies are sitting on the document goldmine. Thinking of which some are PDFs, emails, customer feedback, patents, contracts, technical documents, sensitive documents, HR files and the list goes on. These documents are only going to grow with time. Making sense of each document is difficult since a lot of these documents are Continue Reading

MachineX: Logistic Regression with KSAI

Reading Time: 2 minutes Logistic Regression, a predictive analysis, is mostly used with binary variables for classification and can be extended to use with multiple classes as results also. We have already studied the algorithm in deep with this blog. Today we will be using KSAI library to build our logistic regression model. Setup


Reading Time: < 1 minute Hi all, Knoldus has organized a 30 min session on 27th April 2018 at 4:00 PM. The topic was NAIVE BAYES CLASSIFIER. Many people have joined and enjoyed the session. I am going to share the slides here. Please let me know if you have any question related to linked slides.

MachineX: One more step towards NAIVE BAYES

Reading Time: 4 minutes I hope we understand the conditional probabilities and Bayes theorem through our previous blog. Now let’s use this understanding to find out more about the naive Bayes classifier. NAIVE BAYES CLASSIFIER Naive Bayes is a simple technique for constructing classifiers: models that assign class labels to problem instances, represented as vectors of feature values, where the class labels are drawn from some finite set. Naive Bayes Continue Reading

MachineX: Unfolding Mystery Behind NAIVE BAYES CLASSIFIER

Reading Time: 4 minutes In machine learning, Naive Bayes classifiers are a family of simple “probabilistic classifiers “based on applying Bayes’ theorem with strong (naive) independence assumptions between the features. The Naive Bayes Classifier technique is based on the so-called Bayesian theorem and is particularly suited when the dimensionality of the inputs is high. Despite its simplicity, Naive Bayes can often outperform more sophisticated classification methods.   In simple terms, a Naive Bayes classifier assumes that Continue Reading

Learning Classification using SMILE

Reading Time: 2 minutes After an introduction to SMILE, lets go through the various steps necessary for its implementation. You may refer to the blog for an introduction to SMILE. What can be most important thing for implementing any Machine Learning algorithm ? The answer is really easy. Data is primarily the most important thing as Machine Learning involves building models from data. So it is required to play Continue Reading