Winning a Kaggle Competition in Python
Learn how to approach and win competitions on Kaggle.
Learn how to approach and win competitions on Kaggle.
Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.
Learn the bag of words technique for text mining with R.
Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.
This course covers everything you need to know to build a basic machine learning monitoring system in Python
From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.
Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.
Leverage the tools in the tidyverse to generate, explore and evaluate machine learning models.
Learn how to build a model to automatically classify items in a school budget.
Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.
Learn how to tune your model's hyperparameters to get the best predictive results.
Learn to detect fraud with analytics in R.
In this course you'll learn how to apply machine learning in the HR domain.
Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.
Learn to process sensitive information with privacy-preserving techniques.
Learn how to prepare and organize your data for predictive analytics.
In this course you'll learn how to use data science for several common marketing tasks.
Learn how to predict click-through rates on ads and implement basic machine learning models in Python so that you can see how to better optimize your ads.
Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.