Don't be naive when it comes to building machine learning models. Despite the unprecedented speed and ease of creating predictive models in modern tools, the human mind is still essential for generating good models. From selecting the right problem to solve to preventing algorithm bias, machine learning is still an art and a science. To reap the benefits of artificial intelligence and machine learning, we will share the most common mistakes – and battle-proven practices – to help you build better models.
You will learn:
- About selecting the right problem
- About providing adequate data
- About preventing algorithm bias