Machine Learning courses

4.18

This capstone project course for the Recommender Systems Specialization brings together everything you've learned about recommender systems algorithms and evaluation into a comprehensive recommender analysis and design project. You will be given a...

5

Train and evaluate decision trees and random forests for regression and classification. Train and evaluate support-vector machines (SVM) for regression and classification. Train and evaluate multi-layer perceptron (ML) artificial neural networks (ANN...

4.67

This course takes you from understanding the fundamentals of a machine learning project. Learners will understand and implement supervised learning techniques on real case studies to analyze business case scenarios where decision trees, k-nearest ne...

4.51

Prepare data, detect statistical data biases, and perform feature engineering at scale to train models with pre-built algorithms.

Evaluating Clinical Decision Support SystemsBias, Calibration and Fairness in Machine Learning ModelsDecision Curve Analysis and Human-Centred Clinical Decision Support SystemsPrivacy concerns in Clinical Decision Support Systems

4.39

Develop inclusive strategies to clearly communicate the business impacts of ethical risks to diverse stakeholders. Design communication strategies that are diverse, equitable, and inclusive. Design a crisis communication plan to manage internal and e...

4.66

In this course, you will: - Assess the challenges of evaluating GANs and compare different generative models - Use the Fréchet Inception Distance (FID) method to evaluate the fidelity and diversity of GANs - Identify...

4.58

Machine learning is at the core of artificial intelligence, and many modern applications and services depend on predictive machine learning models. Training a machine learning model is an iterative process that requires time and compute...

Data privacy has never been more important. But how do you balance privacy with the need to gather and share valuable business insights? In this course, you'll learn how to do just that, using the...

5

Describe how machine learning applications can address real-world investment problemsExplain machine learning concepts and techniques to a non-expert audienceUtilize the language of data science when working with data scientists and data engineersApp...

4.18

This is the second course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow...

Building good models only succeeds if you have a decent base table to start with. In this course you will learn how to construct a good base table, create variables and prepare your data for...

4.66

Solve time series and forecasting problems in TensorFlowPrepare data for time series learning using best practicesExplore how RNNs and ConvNets can be used for predictionsBuild a sunspot prediction model using real-world data

From a machine learning perspective, regression is the task of predicting numerical outcomes from various inputs. In this course, you'll learn about different regression models, how to train these models in R, how to evaluate...