Dear readers,
Are you ready to learn some additional data science Friday? If yes, then this week’s DataHour can help you do so. Brush up your skills with our industry expert Mohammad Shahebaz, Data Scientist at DataRobot. In this edition of DataHour, learn to deploy a deep learning model in production. The purpose of creating a machine learning model is to address a problem, and a model can only address a problem when it is in use and produced by customers. Model deployment is, therefore just as crucial as model building. So, what are you waiting for? Register yourself and keep your laptops ready to learn data science applications.
Effectively implementing machine learning models is more of an art than a science. Data scientists excel in building models that describe and predict real-world data. The purpose of creating a machine learning model is to address a problem, and a model can only address a problem when it is in use and actively being produced by customers.
A data science professional takes all of the decisions, from determining the best-fitted model for the use case to selecting a model with low latency, reliability, and edge-case handling.
So, if you are willing to learn about practices and methods that will help get machine learning models into production with different techniques, use cases, and the pros and cons of each method.
Prerequisites for registering: Enthusiasm to learn Data Science
Mohammad Shahebaz
Data Scientist at DataRobot
Shahebaz is a Kaggle Grandmaster and Data Scientist at DataRobot. He has experience building accurate, value-generating models that are scalable, creating an impact on millions of users with expertise in building state-of-the-art models from the latest research, creative feature engineering, and building continuous training pipelines with live model monitoring in production.
So, if you want to add new skills to your resume, then Register now and grab this amazing opportunity to learn with the experts. If you’re attending this session and have some questions about this topic, please send them to us at [email protected], or ask directly to the speaker during the session.
If you missed any past episodes of ‘The DataHour,’ you may watch the recordings on our YouTube channel or read the synopsis here.
If you’re having trouble enrolling or would like to conduct a session with us. Contact us at [email protected]