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Name: Feature Engineering for Machine Learning
Rating: 4.47 (77 reviews)

Feature Engineering for Machine Learning

4.47 Beginner level 1.5 learning hrs 901 Learners

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Skills you will gain

Introduction to Feature Engineering

Under sampling

Over sampling

Key Highlights

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About this course

Feature Engineering is to extract the features from the data and substitute them in the algorithms.This course will help you to understand the concept of upsampling, downsampling, SMOTE, etc. Also, the course will help you understand to build the model using logistic regression and make you understand the confusion matrix.

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Course outline

Introduction to Feature Engineering

Concept of Undersampling and Oversampling

Hands-on exercise showing tuning of model

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Feature Engineering for Machine Learning

4.47

1.5 Hours

Beginner

901 learners enrolled so far

Get free course content

Master in-demand skills & tools

Test your skills with quizzes

Trusted by 10 Million+ Learners globally

4.6

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4.94

4.7

Learner reviews of the Free Courses

4.47

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77%

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10%

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Vishal Randhawa

5.0

★★★★ ★

United Arab Emirates

“Insightful and Well-Structured Course”

I enjoyed the detailed curriculum and the instructor's teaching approach. The quizzes and assignments were challenging and helped solidify my understanding of feature engineering concepts. The course is easy to follow and perfect for anyone looking to dive deeper into this topic. Highly recommended!

Bandana Tigela

5.0

★★★★ ★

“Comprehensive Guide to Feature Engineering and Model Tuning”

I enjoyed the thorough explanation of feature engineering and how it relates to improving model accuracy. The course also did a great job of covering model tuning with practical examples. I would have liked more exercises using diverse datasets to deepen my understanding further.

Abdul Karim Abdul Qadir Ghulam Haidar

5.0

★★★★ ★

“Good and very informative course helped me a lots”

The course was incredibly helpful in introducing me to the basics of machine learning. I particularly enjoyed the hands-on projects, which allowed me to practice key concepts like model evaluation and feature engineering. The content was well-structured, although I would have liked a deeper dive into hyperparameter tuning and model optimization. The instructor was clear and engaging, making complex topics accessible. I feel more confident in applying machine learning techniques to real-world problems, and I look forward to building more projects in the future

Kashif Ahmed

5.0

★★★★ ★

“Skills enhancing course and such a great opportunity”

An introduction to feature engineering course provides foundational skills crucial for transforming raw data into meaningful inputs for machine learning models. By learning how to select, modify, and create features from data, participants gain the ability to improve model accuracy and performance. The course covers techniques for handling various data types, dealing with missing values, and extracting relevant patterns, which enhances the effectiveness of predictive analytics and data-driven decision-making. With these skills, individuals can optimize model training processes, reduce overfitting, and ultimately deliver more insightful and actionable results, making it a valuable asset for data scientists and analysts across diverse industries.

What our learners enjoyed the most

Instructor

70%

70% of learners liked instructor's teaching style

Skill & tools

63%

63% of learners found all the desired skills & tools

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