RARE TechnologiesGLG’s On-Site Machine Learning Training
OVERVIEW OF THE DELIVERED TRAINING
GLG (Gerson Lehrman Group) is the world’s largest membership network for one-on-one professional learning. The organization’s expert membership comprises more than 425,000 thought leaders and practitioners serving users at more than 1,400 client companies located in 40 countries. Professionals working with GLG have countless options to learn, make better decisions, and grow.
RaRe Technologies instructors taught GLG teams smart, efficient practices for building, improving and deploying scalable natural language processing systems (NLP) using Python, using existing software libraries to avoid wasting time or trying to reinvent the wheel.
All course materials were customized to focus on the business’ real challenges and products in development.
A combination of teaching and hands-on programming exercises gave attendees the opportunity to apply, test and refine their knowledge, improving retention and building confidence through real-time feedback.
The Business Challenge
GLG came to RaRe to help mitigate the knowledge gap the IT team felt was developing within the organization with regards to Machine Learning and Python.
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The main goal was to immerse our team in new tools for Python and Machine Learning for them to use across the many IT projects we have activated at GLG.
Will Ballard, CTO at GLG.
How RARE HELPED
By the end of this 2-day intensive workshop, participants had the necessary skills to:
- Write robust document processing pipelines using best industry practices
- Understand capabilities and limitations of existing NLP tools and algorithms for semantic analysis
- Apply algorithms for entity extraction, chunking, semantic indexing and document retrieval
- Communicate modelling results to stakeholders and provide meaningful insights into the data
- Optimize CPU and memory of existing or developing Topic Modelling systems
- Integrate with non-Python data mining tools and services
THE COURSE
Attendees included a diverse array of resources from the GLG IT team including developers and data scientists from multiple global locations. Additionally, a live stream was provided for the team members that could not make it to the New York facility.
Gordon Mohr, Senior Training Consultant at RaRe Technologies, facilitated the Practical Machine Learning course, RaRe’s hands-on training for programmers and data scientists who desire an improving proficiency in data mining and Python in general.
Proficiency in Python is critical for streamlining the data modeling process and is the gateway to the application of Machine Learning to solve GLG’s business problems.
This two-day intensive was customized to include immersive projects on data exploration, feature engineering, pipelines, error analysis and production models working through GLG’s actual real world use cases.
THE RESULTS
“Knowledge of the latest tools and techniques in this fast moving field is critical for my team. RaRe delivered a focused training which produced valuable hands-on project work. I look forward to working with them again.” Will Ballard, CTO at GLG
The developers from GLG’s IT team who participated in RaRe’s comprehensive Practical Machine Learning training learned to set up and manage the machine learning process, from input data munging to data analysis and visualizations, progressing to modeling, error analysis and integrations.
Each attendee gained new insights by using popular Python tools such as pandas , scikit-learn and gensim, as they completed instructor-lead, data-mining projects on actual company data.
The CTO, Will Ballard, accomplished his goal of bringing an immersive, hands-on, project-lead training to GLG, reinforcing the relevance of Python and Machine Learning as valuable tools for their organization.
INTERESTED IN BUILDING YOUR ORGANIZATIONS MACHINE LEARNING CHOPS?
RaRe experts train teams to master Machine Learning and apply new skills directly to their work.
The results are immediate.
Get in Touch to advance the Machine Learning expertise of your organization.
