Machine Learning

5 courses

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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This learning path includes:

5 courses with bite-sized lessons and practices

32 engaging lessons in text and video formats

119 hands-on practices

One-on-one guidance from Cosmo, our AI tutor

Verified skills you'll gain

INTERMEDIATE

Data Cleaning and Preprocessing

INTERMEDIATE

Feature Engineering

ADVANCED

Machine Learning Model Development

DEVELOPING

Deep Learning and Neural Networks

Tools you'll use

Numpy

Pandas

Python

Scikit-learn

TensorFlow

Trusted by learners working at top companies

7 lessons

26 practices

Data Cleaning and Preprocessing in Machine Learning

Explore essential machine learning preparation using the Titanic Dataset. Gain skills in cleaning and preprocessing historical data with Python and Pandas, readying it for ML models and accurate analytics.

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7 lessons

26 practices

Foundational Machine Learning Models with Sklearn

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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6 lessons

21 practices

Feature Engineering for Machine Learning

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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6 lessons

23 practices

Intro to Model Optimization in Machine Learning

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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6 lessons

23 practices

Introduction to Neural Networks with TensorFlow

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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Meet Cosmo: The smartest AI guide in the universe

Our built-in AI guide and tutor, Cosmo, prompts you with challenges that are built just for you and unblocks you when you get stuck.

Whether you’re leveling up or just starting out, find your next step here.