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Tag: CATBoost

CatBoost: A Solution for Building Model with Categorical Data

Introduction If enthusiastic learners want to learn data science and machine learning, they should learn the boosted family. There are a lot of algorithms that...

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Understanding by Implementing: Decision Tree

Image by Author  Many advanced machine learning models such as random forests or gradient boosting algorithms such as XGBoost, CatBoost, or LightGBM (and even autoencoders!) rely...

Hyperparameter Optimization: 10 Top Python Libraries

Image by Author  Hyperparameter optimization plays a crucial role in determining the performance of a machine learning model. They are one the 3 components of...

Explainable AI: 10 Python Libraries for Demystifying Your Model’s Decisions

Image by Author  XAI is artificial intelligence that allows humans to understand the results and decision-making processes of the model or system. Pre-modeling Explainability Explainable...

Top 100 Data Science Interview Questions

Introduction Data science is a rapidly growing field that is changing the way organizations understand and make decisions based on their data. As a result,...

Introduction to Synthetic Control Using Propensity Score Matching

This article was published as a part of the Data Science Blogathon. Here’s a secret, synthetic control methods can solve this problem with utmost...

Ultimate Guide To Boosting Algorithms

Introduction Hi everyone! This is the 4th article of the series of data science interview questions. In case you want to revisit the previous ones,...

How is machine learning utilized for time series forecasting?

Time series forecasting is one of the key topics of machine learning. The fact that so many prediction issues have a temporal component makes...

Amazon SageMaker JumpStart models and algorithms now available via API

In December 2020, AWS announced the general availability of Amazon SageMaker JumpStart, a capability of Amazon SageMaker that helps you quickly and easily get started with machine learning (ML). JumpStart provides one-click fine-tuning and deployment of a wide variety of pre-trained models across popular ML tasks, as well as a selection of end-to-end solutions that […]

Let’s Find Out How to Make Engaging Videos?

This article was published as a part of the Data Science Blogathon. Introduction In this article, we will be predicting how engaging a video can be at the user level. We have been provided with a dataset that contains that user’s earlier videos engagement score along with their personal information. We will build multiple regression models […]

The post Let’s Find Out How to Make Engaging Videos? appeared first on Analytics Vidhya.

Guide On Customer Churn: Don’t Just Predict, Prevent it!

This article was published as a part of the Data Science Blogathon. Introduction Phonepe, Google Pay (Tez) are ubiquitous names in the Indian payment ecosystem and the top two players in the area. According to Phonepe pulse report, it has133 million monthly active users as of July’21. For the Q3-21 quarter, the total transactions were 526.8 Cr […]

The post Guide On Customer Churn: Don’t Just Predict, Prevent it! appeared first on Analytics Vidhya.

3 Reasons Why Data Scientists Should Use LightGBM

There are many great boosting Python libraries for data scientists to reap the benefits of. In this article, the author discusses LightGBM benefits and how they are specific to your data science job.

How Machine Learning Works in Paid Marketing?

Paid marketing is getting more complex and competitive as more players are entering the online domain. Knowing how to run ads is not enough...

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