The 2nd Annual Machine Learning in Quantitative Finance covers topics such as:
- Overcoming issues surrounding data quality in ML models
- The best use cases for ML in quantitative finance
- New methods to explain and interpret ML results to stakeholders
- The best utility of alternative data within quantitative strategies
- Comparing recruitments approaches to attract and hire ML experts
The 2nd Annual Machine Learning in Quantitative Finance brings together Head of:
- Quantitative Investments
- Quantitative Research
- Quantitative Investment Research
- Quantitative Analytics
- Model Development (in investment banking)
- Quantitative Research for Equities/Fixed Income/Multi Assets
