Course - Get Started in Machine Learning with Python scikit-learn


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Course Name: Get Started in Machine Learning with Python scikit-learn.

Learn the science of discovering patterns and making intelligent predictions from big data. 5 day bootcamp designed to help you learn basic principles needed to understand and apply Machine Learning models and methods using Python Scikit-Learn.

For corporate bookings or to organize on-site training email hello@persontyle.comor call now +44 (0)20 3239 3141

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Course - Get Started in Machine Learning with Python scikit-learn

  1. 1. © 2014 Persontyle Ltd. All rights reserved. GET STARTED IN MACHINE LEARNING WITH PYTHON SCIKIT-LEARN 5 DAY BOOTCAMP 21-25 JULY 2014, LONDON
  2. 2. Data generated through our activities captures plethora of information about our identity, likes and dislikes etc. This information has tremendous value in every aspect of human life. Programming computers to unravel this hidden information is what Machine Learning is all about. It is the art and science of scientifically deriving insights, patterns and predictions from data.© 2014 Persontyle Ltd. All rights reserved. <MACHINE LEARNING> “The field of machine learning is concerned with the question of how to construct computer programs that automatically improve with experience.” - Tom Mitchell Machine Learning models and programs automatically make decisions from data in order to achieve some goal or requirement. Machine learning models matter to the world. Because they are; #EFFICIENT Machine Learning models predict and detect partners faster than any other manual program or method. #EFFECTIVE Machine Learning models can do better job than humans when analysing and predicting large scale and streaming data sets (big data). #SCALE Machine Learning models can provide solutions to large data problems that traditional systems can not solve. LEARN THE SCIENCE OF DISCOVERING PATTERNS AND MAKING INTELLIGENT PREDICTIONS FROM BIG DATA
  3. 3.© 2014 Persontyle Ltd. All rights reserved.  Machine perception  Computer vision, including object recognition  Natural language processing  Pattern recognition  Search engines  Medical diagnosis  Bioinformatics  Brain-machine interfaces  Detecting credit card fraud  Stock market analysis  Classifying DNA sequences  Sentiment analysis  Affective computing  Information retrieval  Recommender systems MACHINE LEARNING CAN APPEAR IN MANY GUISES Examples in the real world include handwritten recognition, weather prediction, fraud detection, search, facial recognition, and so forth are all examples of machine learning in the wild. Applications for Machine Learning include: “Over the past two decades Machine Learning has become one of the mainstays of information technology and with that, a rather central, albeit usually hidden, part of our life. With the ever increasing amounts of data becoming available there is good reason to believe that smart data analysis will become even more pervasive as a necessary ingredient for technological progress.” DR. ALEXANDER J. SMOLA, PROFESSOR, CARNEGIE MELLON UNIVERSITY
  4. 4. Why write programs when the computer can instead learn them from data? In this 5 day bootcamp you will learn how to make this happen. Though it has been an area of active research for over 50 years, Machine Learning is currently undergoing a renaissance driven by Moore's law and the rise of big data. Large private and public investment in the area has given us self driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Computer based machine learning algorithms now outperform humans on tasks such as handwritten digit recognition, traffic sign recognition, and even on some complex reasoning tasks as demonstrated by IBM's Watson winning Jeopardy. Bootcamp is designed to help you learn basic principles needed to understand and apply Machine Learning models and methods using Python Scikit-Learn. Lots of hands-on examples to step through real-world application of Machine Learning. Attending this bootcamp will enable you to understand the basic concepts, become confident in applying the tools and techniques, and provide a firm foundation from which to explore more advanced methods.© 2014 Persontyle Ltd. All rights reserved. [5 day bootcamp to learn basic building blocks of practical Machine Learning] GET STARTED IN MACHINE LEARNING WITH PYTHON SCIKIT-LEARN “In a way Machine Learning has become the new black gold. The application areas are literally endless and from where we stand we haven't even reached the inflection point. If you think about it, there are many industries out there that are just waking up to the reality of big data and data science.” MARTIN HACK, CEO SKYTREE Python and scikit-learn logos are the property of their respective owners
  5. 5. WHAT WILL YOU LEARN? Attend the bootcamp to learn the basic concepts, models and techniques required to perform practical Machine Learning. GET STARTED IN MACHINE LEARNING© 2014 Persontyle Ltd. All rights reserved. DAY 1 Understand how the structure and function of the human brain is different from a computer and how this affects learning in each. Define Machine Learning, why it matters, and discuss its relationship to data mining, data science, and statistics. Understand the steps in the machine learning pipeline, from data acquisition and feature generation, to training and model selection. Overview of core Machine Learning terminology i.e. features, instance, model selection, bias, variance, generalization, precision, etc. Review of the fundamentals of linear algebra, calculus, statistics, and probability theory. DAY 2 Doing Machine Learning - Review fundamentals of practical Machine Learning • Reading the data and cleaning it. • Exploring and understanding the input data. • Analysing how best to present the data to the learning algorithm. • Choosing the right model and learning algorithm. • Measuring the performance correctly. Basics of Python programming language and environment. Scientific Python building blocks and workflow • NumPy: Base n-dimensional array package • SciPy: Fundamental library for scientific computing • IPython: Enhanced interactive console • Pandas: Data structures and analysis Overview of Scikit-learn: Machine Learning in Python Our first Machine Learning Application - K Nearest Neighbours Labs • Setting up the environment • Python programing basics (load data, simple histogram, select rows, columns, scatter plot, simple stats, ...) • Linear Regression
  6. 6. WHAT WILL YOU LEARN? GET STARTED IN MACHINE LEARNING© 2014 Persontyle Ltd. All rights reserved. DAY 3 Generally Applied Algorithms and Applications • Naive Bayes • Support Vector Machines • Logistic Regression • Decision Trees Labs • Detecting Spam using Machine Learning • Predicting house prices with regression • Image recognition with Support Vector Machines DAY 4 Dimensionality Reduction - Reducing the number of random variables to consider • Feature selection and feature extraction methods • Principal Component Analysis Clustering - Automatic grouping of similar objects into sets. • Overview of clustering methods • Applications and Algorithms Basics of Crab - Recommender systems in Python BigML - Putting the power of Machine Learning in your hands Labs • Dimensionality reduction practical example • Clustering handwritten digits with k-means Python and scikit-learn logos are the property of their respective owners.
  7. 7. WHAT WILL YOU LEARN? GET STARTED IN MACHINE LEARNING© 2014 Persontyle Ltd. All rights reserved. DAY 5 Model Selection and Evaluation in Scikit-learn - Comparing, validating and choosing parameters and models Overview of Pre-processing in Scikit-learn - Feature extraction and normalization. Putting it all together - Final Kaggle Project Current Hot Topics • Large scale Machine Learning • Deep Learning • Watson style learning • Probabilistic programming • Machine Learning as a Service WHO SHOULD TAKE THIS COURSE? You are interested in Machine Learning. You have read a book or taken an online course and now want to know more and learn how to apply Machine Learning to solve real problems. Well-suited to machine learning beginners or those with some experience. All Machine Learning Enthusiasts Business Professionals Technologists/ Developers Data/Market/ Research Analysts Business/ Technology Consultants PREREQUISITES Basic understanding of calculus, statistics, probability theory, linear algebra. This will be refreshed but not in detail. Basic knowledge of python is required. All lab sessions will be done using IPython notebooks and Scikit-learn.
  8. 8. Persontyle trainers are passionate about meeting each participants learning needs. They have been chosen both for their extensive practical Data Science and Machine Learning experience and for their ability to educate and interact with natural empathy. All of our trainers have worked on a variety of data science and Machine Learning projects. They share their academic knowledge and real- world experience and each individual adds their own unique perspective to the course. Our trainers present in a style that is informal, entertaining and highly interactive. Guest Speakers Business leaders, Machine Learning practitioners, and academic researchers covering use cases, case studies and sharing practical experience of applying Data Science and Machine Learning in their organizations. COURSE INSTRUCTORS “A breakthrough in Machine Learning would be worth ten Microsofts” BILL GATES, CHAIRMAN, MICROSOFT© 2014 Persontyle Ltd. All rights reserved. GET STARTED IN MACHINE LEARNING WHAT SHOULD I BRING? Along with bringing your laptop and charger, don’t forget to bring loads of curiosity, scepticism, eagerness to participate and the desire to learn.
  9. 9. THE SCHOOL OF DATA SCIENCE The School of Data Science, a project of Persontyle, specializes in designing and delivering structured, relevant, practical and affordable learning experiences for all of us to understand data science in simple human terms. RETURN ON INVESTMENT (ROI) CONVINCE YOUR BOSS We all need to learn how to analyse data, find the value and glean insights. The advent of the data driven connected era means that analyzing massive scale, messy, noisy, and unstructured data is going to increasingly form part of everyone's work. The School of Data Science learning programs provide a unique investment opportunity that pays for itself many times over. For corporate bookings or to organize on-site training email or call now +44 (0)20 3239 3141 World-class Instructors Develop Practical Data Science Skills Real World Industry Use Cases Short Courses For Time Convenience Value For Money Register Now Limited seats. We encourage you to register as soon as you can. Follow us on Twitter @schooltds Like us on Facebook Get in touch! "For the best return on your money, pour your purse into your head." - Benjamin Franklin