intermediate

Journey into Machine Learning with Sklearn and Tensorflow

Embark on a comprehensive journey into the world of machine learning. This path starts with the fundamentals of Machine Learning using Sklearn and then progresses to advanced concepts in deep learning through Tensorflow.

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Verified skills you'll gain

INTERMEDIATE

Data Cleaning and Preprocessing

DEVELOPING

Deep Learning and Neural Networks

INTERMEDIATE

Feature Engineering

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Course 2

Foundational Machine Learning Models with Sklearn

7 lessons

26 practices

Learn fundamental machine learning models with Sklearn, centered on the Iris Dataset. This course covers key algorithms like linear and logistic regression, and decision trees. Master implementation, evaluation, and optimization to pave the way for advanced machine learning concepts.

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Course 3

Feature Engineering for Machine Learning

6 lessons

21 practices

Explore feature engineering using UCI's Abalone Dataset in this course. Enhance your skills in feature extraction, selection, and transformation to boost machine learning model performance. Learn to craft valuable features, apply different selection strategies, and use feature combinations to uncover data patterns.

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Course 4

Intro to Model Optimization in Machine Learning

6 lessons

23 practices

Delve into machine learning fundamentals using the Wisconsin Breast Cancer Dataset. This course focuses on key ML techniques like data exploration, model tuning, and evaluation. Master hyperparameter tuning, regularization, and ensemble methods through practical exercises to boost your predictive models' accuracy and reliability.

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Course 5

Introduction to Neural Networks with TensorFlow

6 lessons

23 practices

Start your exploration of neural networks with a beginner's course on TensorFlow, using the scikit-learn Digits Dataset. Learn neural network basics and deep learning by developing, training, and evaluating models with TensorFlow. Understand different neural network architectures and improve them, emphasizing the importance of data preparation in deep learning.

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I love that it's personalized. When I'm stuck, I don't have to hope my Google searches come out successful. The AI mentor Cosmo knows exactly what I need.

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Senior Machine Learning Engineer

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I'm impressed by the quality and can't stop recommending it. It's also a lot of fun!

Francisco Aguilar Meléndez

Data Scientist

+11

From our community

Hear what our customers have to say about CodeSignal Learn

I'm impressed by the quality and can't stop recommending it. It's also a lot of fun!

Francisco Aguilar Meléndez

Data Scientist

+11

I love that it's personalized. When I'm stuck, I don't have to hope my Google searches come out successful. The AI mentor Cosmo knows exactly what I need.

Faith Yim

Software Engineer

+14

It's an amazing product and exceeded my expectations, helping me prepare for my job interviews. Hands-on learning requires you to actually know what you are doing.

Alex Bush

Full Stack Engineer

I'm really impressed by the AI tutor Cosmo's feedback about my code. It's honestly kind of insane to me that it's so targeted and specific.

Abbey Helterbran

Tech consultant

I tried Leetcode but it was too disorganized. CodeSignal covers all the topics I'm interested in and is way more structured.

Jonathan Miller

Senior Machine Learning Engineer

+12

I'm impressed by the quality and can't stop recommending it. It's also a lot of fun!

Francisco Aguilar Meléndez

Data Scientist

+11