Model deployment is the next and very important steps once you finalized your model training and development. There are many methods available to deploy the models depending upon the type of serving. There are many serving methods like batch serving, online serving, real time serving or live streaming based serving. In this article I am going to explain one of the deployment mechanism which does online serving using APIs. So I will be explaining how to deploy models using Docker container and run them on production efficiently and reliably.
Author: Ashutosh Tripathi
Linear Regression Interview Questions and Answers
While working in regression analysis, you should be familiar with some very basic but very impactful concepts. In machine learning interviews, you can always expects questions from regression analysis. Regression analysis also develop the basic understanding of machine learning model building as we mostly start our machine learning journey from regression analysis only.
Feature Store in Machine Learning
Feature store in machine learning is the concept to store features in both online and offline stores for model training and serving purposes. Feature store make sure to provide the consistency between the data used for model training and the data used during online serving to models. In other words, it guarantees that you’re serving the same data to models during training and prediction, eliminating training-prediction skew. Feast is one of the open source tools used for feature store.
Experiment Tracking using MLFlow in Machine Learning
Experiment tracking is the process of recording all the important components such as hyper parameters, metrics, models and artifacts like plots PNG images, files etc. Experiment tracking helps to reproduce the old results by using the stored parameters.
Practice Problems on Hypothesis Testing
Hypothesis testing helps us to validate the various claims made by different people in different scenario. For example if we claim that there is no significant difference between boys and girls intelligence level. So can we validate it significantly? Or can we validate that smoking causes cancer?
View post to subscribe to site newsletter.
A Complete Guide to Decision Tree Formation and Interpretation in Machine Learning
Decision Tree is supervised machine learning algorithm which is used for both types of problems regression (that is predicting the continuous value for future example house price, hours the match can be played given overcast condition etc…) and classification (that is classifying different objects into respective categories or classes for example given the overcast conditions match will be played or not, given image belongs to cat or dog etc…).