Any sound data science pipeline prioritizes gathering clean, trusted, and accessible data before diving into a machine learning project. Ensuring quality data also inspires credibility and promotes adoption of data-driven practices. How do you ensure your data checks these boxes?Learn More
How Research Meets Practice: 2022 Machine Learning Trends and Techniques
Through the lens of three real-world data science projects, discover promising ML trends and techniques for 2022 and beyond.
As demand for the data scientist role remains high, the onus is on data scientists to find ways to differentiate themselves amidst a sea of competition. In this webinar, data scientists will be able to gain key statistics and probability concepts to increase their understanding of machine learning models, experimental design, and bring a new perspective to their projects.Learn More
Trends on how companies are identifying the right data to train AI and machine learning algorithms accurately to tackle various issues such as personalization and fraud with increased speed and agility.Learn More