Author: Sanjay Kumar

Table of Contents

• Introduction
• Installation of the LazyPredict Module
• Implementing LazyPredict in a Classification Model
• Implementing LazyPredict in a Regression Model
• Conclusion

Introduction

The development of machine learning models is being revolutionized by the state-of-the-art Python package known as LazyPredict. By using LazyPredict, we can quickly create a variety of fundamental models with little to no code, freeing up our time to choose the model that would work best with our data.

Model selection may be made easier using the library without requiring considerable parameter adjustment, which is one of its main benefits. LazyPredict offers a quick and effective way to find and fit the best models to our data.

Table of Contents

• Introduction
• Installation of dependencies  and importing of Blenderbot model
• Chatting with the model
• Conclusion
• References

Introduction

In Artificial Intelligence, Blenderbot comes under the category of conversational agents. A conversational agent, or CA, is a computer program designed to have a conversation with a person, according to Wikipedia. In other words, conversational agents are automated systems — often driven by artificial intelligence — that are designed to have natural-language conversations with people.

Table of Contents

• Introduction
• What is AutoML?
• Why is AutoML the need of the future?
• Various AutoML Platforms
• Will AutoML replace data scientists?
• Conclusion
• References

Introduction

An old idea that has changed everything is automation. Every tool and method we have ever created, in one way or another, involves some level of automation. An emerging field known as automated machine learning, or AutoML, automates the process of creating machine learning models to model data. With the best AutoML for ML projects, machine learning projects are now incredibly simple to finish. Both novices and experts can benefit greatly from using AutoML libraries for machine learning applications at any moment without risk of error. These libraries are well-known for offering resources to automatically identify the top machine learning initiatives for a task involving predictive modeling. Let’s explore some of the top ten AutoML libraries for machine learning projects that are becoming popular among researchers in recent times.