Machine Learning Interview questions and answers part 2 | ML Faq

This post is part 2 in the series of frequently asked Machine Learning Interview Questions and Answers. Machine Learning Frequently asked Interview Questions and Answers Part 2

1. What is Feature Scaling and why and where it is needed?
2. Normalization vs Standardization
3. What is the bias-variance trade-off?
4. Define the Overfitting problem and why it occurs?
5. What are the methods to avoid Overfitting in ML?

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How to deploy machine learning models as a microservice using fastapi

As of today, FastAPI is the most popular web framework for building microservices with python 3.6+ versions. By deploying machine learning models as microservice-based architecture, we make code components re-usable, highly maintained, ease of testing, and of-course the quick response time. FastAPI is built over ASGI (Asynchronous Server Gateway Interface) instead of flask’s WSGI (Web Server Gateway Interface). This is the reason it is faster as compared to flask-based APIs.

How Machine Learning changing the traditional ways of developing a mobile app

The term Machine Learning was given by Arthur Samuel in the year 1959 and he defined it as the “field of study that gives computers the ability to learn without being explicitly programmed”. Now Machine Learning is helping organizations to take data driven decisions rather completely relying on the experience driven decisions.

Further in this article, we will discuss the benefits of Machine Learning in the development process of a mobile app and everything which revolves around Machine Learning and its use in developing a mobile app.

A Step by Step Guide to Logistic Regression Model Building using Python | Machine learning

In the field of Machine Learning, logistic regression is still the top choice for classification problems. It is simple yet efficient algorithm which produces accurate models in most of the cases. In its basic form, it uses the logistic function to calculate the probability score which helps to classify the binary dependent variable to its respective class. Logistic regression is the transformed form of the linear regression. In this post I have explained the end to end step involved in the classification machine learning problems using the logistic regression and also performed the detailed analysis of the model output with various performance parameters.

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