How to build Machine Learning Models using Logistic Regression

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January 20, Wednesday 19:00 IST
January 21, Thursday 19:00 IST
January 22, Friday 19:00 IST
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Here is What You'll Learn

Understand data extraction, exploration and visualization

There are no shortcuts for data exploration. We cover several data exploration aspects, including missing value imputation, outlier removal and the art of feature engineering

Learn how to prepare data for ML algorithms

Data preparation may be one of the most difficult steps in any machine learning project. The reason is that each dataset is different and highly specific to the project. Nevertheless, there are enough commonalities across predictive modeling projects that we can define a loose sequence of steps and subtasks that you are likely to perform.

Learn how to train and finetune models

There are mainly three different ways in which a pre-trained model can be re-purposed. They are, Feature extraction . Copy the architecture of a pre-trained network. Freeze some layers and train the others.

Learn how to deploy into a serialized object for future use

Serialization is a process 'to arrange in a series and broadcast it to the outer world'. We send a serializing object to the network stream and publish or send it to a directory to store its form for the future use.

Open Q&A and Networking

Lastly, get all our queries resolved with an open Q&A session.


About Fatos Ismali

Fatos is a passionate technologist bringing with him a wealth of experience from both the start-up and corporate worlds. He has a huge interest in Deep Learning and Data Engineering and has seen himself apply his skills in industries such as Financial Services, Retail, Public Sector, Biomass Energy Production, Media and Publishing. Fatos holds a BSc in Computer Science and a Master’s in Data Warehouses and Business Intelligence. He has worked for Oracle as a Cloud Architect and now works for Microsoft as a Data Solutions Architect focusing on Data & AI. He is the founder of one of the biggest Data Science communities in London - Data Science Initiative.

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Available Dates

January 20th
19:00 IST
Watch now
20 Jan, 2021 @ 19:00
21 Jan, 2021 @ 19:00
22 Jan, 2021 @ 19:00