A Step by Step Guide to Implement Decision Tree using Python | Machine Learning

In this we will learn from scratch how to implement decision tree using python. We will solve one classification problem and build the model from scratch. Following are the points we will be covering in this post:
Exploratory Data Analysis – EDA
Data Visualization
Data Pre-processing
Data Spliting- Stratified Sampling
Oversampling – SMOTE
Model Training
Fine Tuning
Hyper parameter Tuning

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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?

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.

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