This course is suitable for: Tech Analysts, S&T Analysts (optionally).
By the end of this course, participants will be able to:
• Compare and contrast random forest and decision tree techniques
• Implement these techniques using standard libraries
• Comment on the efficiency of these methods given limitations in datasets
• Introduction: supervised and unsupervised machine learning, decision trees and random forests
• Implement decision tree in Scikit-Learn (there is no TF implementation to draw on!)
• Implement random forest in TensorFlow (TF does do Random Forests)
• Conclusions: which is the better method? When, and why?
We are thought leaders in instructional and learning journey design and holistic solution architects.
We have extensive finance and investments experience combined with skills application to deliver performance improving results.
We develop immersive learning environments that maximize time to productivity, support talent retention and added value to improving quality of hires.
We are focused on mining the embedded organisational intellectual capital for the benefit of the next generation.
We create and curate best in class practice gathered from our experience with the leading financial institutions.
We design our programmes with the end in mind – what results are you trying to achieve with this intervention? What metrics will we set ourselves to achieve that?
Quality and innovation, using current market and industry best practices, have made us a trusted partner in delivering dynamic and motivating training for the financial and capital markets.
Our programmes are generation proof and responsive to evolving learner needs and styles.
Our solutions use a multi-stakeholder engagement strategy that expands beyond relationships between the learner and learning provider. We create connections with managers, peers and the wider business to drive impactful return on investment..
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The team are so friendly and pleasant to work with, everyone is very professional and keen to help us. Building a relationship over the past couple of years helps us to feel like the Alpha team are even more able to understand our needs and provide more proactive solutions.