Presented By O'Reilly and Cloudera
Make Data Work
5–7 May, 2015 • London, UK

Practical Machine Learning

Angie Ma (ASI), Marc Warner, Andrew Brookes, Anjali Samani, Alessandra Staglianò (The ASI), Ken Williams (The ASI), Mehasan Niranjan, Elena Chatzimichali
9:00 Wednesday, 06 May 2015
9:00 Thursday, 07 May 2015
Location: Hilton Meeting Room 3-6

Learning Objectives

In this course, you will:

  • Gain a broad understanding of the machine learning universe—what is and is not possible with the latest techniques
  • Understand the key elements of the machine learning toolkit
  • Work through the components of a machine learning workflow (data to model to parameters to optimisation to predictions)
  • Learn how to formulate your data into a machine learning problem, and choose the most appropriate technique to solve the problem
  • Experience how machine learning tools provide insight, predictions and allow personalisation
  • Discover how to understand, interpret and convey the results of machine learning
  • Gain the ability to apply machine learning in novel situations
  • Have familiarity with cutting edge techniques, and some perspective on the direction of the field

Description

This intensive two day course will provide you with a condensed introduction to the key concepts and techniques of machine learning. It will allow you to know what is and is not possible with these exciting new tools, and understand how they can benefit your organisation. It will give you the language and framework to talk to both experts and executives.

The course has a strong focus on gaining practical hands-on experience implementing sophisticated algorithms and building predictive models on real datasets. Importantly, you will also learn to evaluate the validity of the model and identify spurious findings. By the end of the two days, you will be ready to implement the algorithms on your own data, and immediately generate value. Finally, you will get a taste of the cutting edge techniques used at the likes of Google, Facebook and Amazon, and guidance on how to further develop your skills.

Topics Covered

Introduction

  • What is Machine Learning?
  • Applications of Machine Learning
  • The Machine Learning Workflow
  • Choosing the right model
  • Forming a prediction

Regression

  • Linear Regression
  • Optimization - Cost Function & Gradient Descent
  • Non-linear regression (polynomial, basis functions)

Probability Theory Basics

  • Estimation from data
  • Confidence in outcomes
  • Bayesian probability and applications

Classification

  • Logistic regression
  • Overfitting and Regularisation
  • Regularised Logistic regression
  • Naive Bayes

Deep Learning

  • Neural Network
  • Forming a topology
  • Optimisation/Backpropagation

Where To Go From Here...

  • Cutting edge machine learning
  • Machine learning at Amazon, Google, Facebook etc.

Ultimately, you will acquire a working knowledge of practical machine learning a set of tools to go away and work on your data.

Target Audience

Machine learning novices

Attendance is limited to 35 participants.

Prerequisites

  • Some familiarity with programming
  • Python desirable but not necessary
  • Understanding of basic calculus desirable but not necessary

About ASI

ASI is a London-based leader in advanced analytics, data strategy, data science and data engineering. We work with our clients to provide bespoke data science training and consulting. In addition, we run a data science fellowship programme for PhDs, where our clients can access the brightest minds for their short term data innovation projects. Our key focus is to help our clients gain competitive advantage by harnessing the power in their existing and untapped data. We enable organisations to become more data driven.

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