Machine Learning is set to become one of the biggest tools for gaining insights from business data. Businesses that adopt machine learning will stand to gain a significant competitive advantage and yet getting started can be a daunting task. In these sessions we aim to take you step by step through the process of setting up a machine learning environment in your business, so your business can also start to benefit from AI.
Artificial intelligence tools and the proliferation of machine learning algorithms to address business problems are becoming more accessible everyday. Many cloud-based platforms now offer numerous machine learning solutions (Azure, Amazon, Google). In addition, these same services bring advanced cloud-based technologies to process and store big data.
Now, more than ever, organisations can take advantage of these systems and become data-driven organisations, gaining deep insights from their data, and use these insights to make critical business decisions that will allow them to become a leader in any industry.
The power of machine learning is the ability of the program to self-learn and investigate multiple patterns within the data simultaneously. This process uncovers trends within the data that were previously indiscoverable by traditional methods.
In a nutshell, computers are able to tap into different types of hidden insights without being explicitly programmed to do so. It does not require someone to understand the data first, with machine learning the understanding of the data comes to you.
Despite these obvious advantages many businesses don't know where to start, or know what needs to be considered.
In this 6-part series, Taysols' Chief Data Scientist will
Who should attend
Anyone, who is considering starting a machine learning project, but doesn't know where to start, which tools and platforms to use or how to select the data.
Each session can be attended independently as different areas will be addressed in each. However, attending all six sessions will give you a comprehensive overview of machine learning and best practice guidance.
To register for the different sessions, please click on the respective link below.
Part 1: Introduction to Machine Learning (31/05/2018)
Part 2: Machine Learning models to choose from (28/06/2018)
Part 3: Available Platforms for Machine Learning (2/08/2018)
Part 4: Machine Learning Tools versus coding models (30/08/2018)
Part 5: Big Data and Machine Learning (27/09/2018)
Part 6: Deep Learning (25/10/2018)
All sessions are free of charge and last approximately one hour. Seats are limited, so register early to secure your seat.