This article examines 5 common mistakes of early Data Scientists. The list was assembled together with Dr. Sébastien Foucaud, who has >20 years of experience in mentoring and leading young Data Scientists in both academia and industry. This post aims to help you better prepare for your work in real-life.
Top 5 mistakes:
- Enter “Generation Kaggle”
- Neural Networks are the cure to everything
3. Machine Learning is the Product
4. Confuse Causation with Correlation
5. Optimize the wrong metrics