EXCEPTIONAL TRAINING COURSES FOR IT PROFESSIONALS
LONDON UK | ONSITE | ONLINE
This course provides advanced-level training on Machine Learning applications developed with Python.
Delegates will learn best practices for building and deploying Machine Learning productsusing Python and its rich ecosystem for scientific computing.
The course is intensive and intended for software developers and software engineers with a working knowledge of Python, who want to improve their proficiency in building data products.
The course should be appealing also to Data Scientists and Data Analysts with a basic knowledge of Python. With practical exercises and interactive discussions, the attendees have the opportunity to apply the proposed concepts on real Data Science applications, building predictive analytics software.
Data Scientists, Mathematicians, Quants or Data Analysts with a basic knowledge of Python.
Machine Learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. Machine Learning algorithms can learn from, and make predictions on data.
With the wealth of data available today, companies can take advantage of Machine
Learning techniques to gain actionable insights and ultimately improve their business.
Using scikit-learn, the core Machine Learning library for Python, attendees will learn how to
implement Machine Learning systems to perform predictions on their data.
We will also examine and use tools and frameworks such as the Open Source TensorFlow.
Data sets come in all sorts of formats and flavours. The first part of a Machine Learning project is understanding the data and the problem at hand.
Data cleaning, data transformation, and in general data pre-processing are the steps to perform in order to get the data sets in the right shape, so Machine Learning algorithms can learn from them.
Python makes data exploration and preprocessing relatively easy.
By injecting domain knowledge in the process, attendees will learn how to extract attributes from the data and how to encode them into features that make Machine Learning algorithms work.
One of the core aspects of applied Machine Learning, feature engineering is difficult and timeconsuming.
The quality and quantity of features can have a great impact on how Machine Learning
algorithms can work.
In supervised learning, the training data consist of a set of training samples associated with a
desired output label. Supervised learning algorithms can learn the desired output from the training data, and make a prediction on new, unseen data.
We'll approach supervised learning from two different directions: classification, the task of
predicting a category, and regression, the task of predicting a quantity.
Examples of applications include price prediction, spam detection and sentiment analysis.
In unsupervised learning, the training data is not labelled. Unsupervised learning algorithms analyse the data and find hidden structures within the data.
We'll approach unsupervised learning in particular from the point of view of a clustering application.
Examples of applications include social network analysis, customer segmentation or product
Using the proper evaluation metrics, we can understand how well our algorithms are performing and we can compare the performances of different algorithms.
Attendees will learn about error analysis and model introspection, in order to “debug” and improve Machine Learning algorithms
See why people choose JBI
12/01/2018: Data analytics courses are the key to the future. The leading current issues in business development are Big Data, AI and Machine Learning, which...
16/01/2018: Big data is a big deal. The huge volume of data generated over just the last decade far exceeds the entire accumulated human data so far. Moreover,...
16/01/2018: As Big Data becomes an integral part of the data-driven enterprise, businesses are encountering problems securing the skills they need to make...
19/10/2017: Nowadays, there is a significant business advantage in being able analyse, process and visualize "big data". While there is no agreed definition...
12/10/2017: The Graduate Programme provided a gateway into technology within investment banking. Graduates (Computer Science, Engineering, Maths, Physics...
13/10/2017: This organisation needed their Supply Chain department to get fully involved with Microsoft’s Power BI reporting product as soon as possible....
Bring a JBI course to your office
and train a whole team onsite
0800 028 6400 or request quote
Get in touch
0800 028 6400
Excellent feedback, consistently !
"great tips help reduce build times"
"we got access to exclusive content"
"Short course meant less time off"
"what an inspiring trainer !"
"colleagues at 2 sites joined via web"
"I passed my exam the next day"