Blockchain Vs. Data Science: What You Need to Know [A Complete Guide]

What is popular between blockchain and big data/data science? A few aspects that quickly struck our minds are that they are both of the best new technologies. Both have the ability to revolutionize the way industry works, and both provide promising career prospects. Blockchain encompasses many of the lucrative coins like BTC, Etherium, free xlm, etc.

Although data science is a comparatively well-established technique, blockchain is at a developing level. Let us explain more about each of them in order to evaluate them better.

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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

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 can cloud computing help organizations adapt to market challenges?

To survive in this COVID-19 age where companies are deliberately looking for the solutions that may help them deal with the business challenges, cloud computing and its associated tools prepare them with cost-effective strategies.

From adapting well to the risks involved in real-time to collaborating well with clients remotely, business entrepreneurs and other experts (either tax or finance) need not hassle for the solutions.

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