Python is a high-level, interpreted, interactive and object-oriented scripting language. Python is designed to be highly readable. In this article we will see
How to install Python on windows,
Verify if it installed correctly and
Create and run one hello-world program.
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 Spliting- Stratified Sampling
Oversampling – SMOTE
Hyper parameter Tuning
ML FAQ Part 1
What is ROC-AUC curve and how to interpret it?
Explain Type I and Type II errors.
What is Precision and Recall?
What is F1 score?
What is the difference between r-square and adjusted r-square values?
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?
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.