AI with “Supervised” Machine Learning (5 days)
by Walid SemaanLanguages: English
Price (from): €1,500 / day
About the trainer:
Walid Semaan is the founder and president of Matrix TRC "Data Science and AI Academy (partners with the SAS Data Science program). He graduated in engineering from Ecole Supérieure d’Ingénieurs à Beyrouth and holds a degree in finance and marketing from the Ecole Supérieure de Commerce de Paris (ESCP) and an MBA from the University Paris-Dauphine-Sorbonne in Paris. He is the creator and architect of the automated analytical artificial intelligence behind “Triple One Analytics,“ winner of the Best Innovative ICT Project at the 2011 Arab Golden Chip Award. Walid is the trainer of all the workshops he wrote, related to research methodologies, data visualization, data analytics, machine and deep learning, quality control, forecasting, epidemiology and big data ecosystem, as well as mostly used proprietary and open-source data analytical tools. Walid joined lately Fleming Events - Europe as an expert trainer in Data Science and is an expert certified trainer in the Middle East for SAS, PWC Academy, MEIRC-PLUS Training, Abu Dhabi Business School, Formatech and Obeikan Digital College. In parallel, he holds thousands of hours teaching master programs at Saint Joseph University, assisting Ph.D. students in their advanced analytics programs, and training local and international companies, to name few from dozens: Central Bank of Lebanon (Lebanon), PWC (Dubai), Vlerick Business School (Belgium), SCAD (Abu Dhabi), OXY Petroleum (Oman), IPSOS (Lebanon), Obeikan Group (KSA), Dallah Hospital (KSA), Smart Dubai (Dubai), DarkMatter (Dubai), Indevco Industries (Lebanon and Egypt) and Algorithm Pharma (Lebanon).
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AI with “Supervised” Machine Learning (5 days) by Walid Semaan
About the training
OVERVIEW
Predictive models have become accessible to all practitioners with the advancement of technologies. Mastering most important predictive models, if not all, is getting closer from automation with prompt comparison of indicators to evaluate the quality of each of them. This course offers a complete overview of “supervised” Machine Learning algorithms, and their role in the enhancement of predictions in most industries. To ensure the practical side, the workshop covers all models under two different technologies (STATISTICA, SAS), allowing participants to become not only expert practitioners, but consultants within their job, by evaluating and choosing the appropriate solution with appropriate technical packages
OBJECTIVES
By the end of this workshop, you will be able to:
- “Learn” the true meaning of Machine Learning
- Comprehend the difference between Data Analysis vs. Machine Learning
- Present the myth and reality of Machine Learning
- Introduce the Testing and Validating samples
- Submit an overview of the world’s best analytics solutions
- Improve classifications with models using more than a variable at a time
- Fine tune estimation with complete predictive models
- Sort out models according to their accuracy level
CONTENT
Multiple Linear Regression
- The model equation
- ANOVA Table
- Coefficient of determination vs. correlation
- Model versus coefficients validation
- Stepwise linear regression
Multiple Logistic Regression
- The model equation
- Model versus coefficients validation
- Odds ratios
- Stepwise logistic regression
Discriminant Analysis
- Discriminant functions:
- Classification functions:
- Mahalanobis Squared distances
- Probabilistic models
Decision Trees
- CART method
- CHAID tree
- Random Forests
- AdaBoost
K Nerest Neighbors
- Types of distances from neighbors
- Rules of classification
- Voting method
Support Vector Machines
- Predictive model
- Estimation model
- Kernel trick
Introduction to Artificial Neural Networks
- Neurons / Weights
- Hidden layers
- Activation functions
Main benefits
- #Wide collection of the biggest experts
- #Filters for all kinds of needs
- #User friendly platform
- #Fast and cheap
- #Highest level of proficiency
More trainings of the trainer
Data Visualization and Descriptive Statistics (3 days) Data Analysis for Professionals (5 days) Data Analysis for Experts (3 days) AI with “Unsupervised” Machine Learning (5 days) Introduction to Deep learning and NLPs for AI applications (3 days) Forecasting Models from A to Z (3 days)