6 Free Workshops on Machine Learning in Python with Scikit-learn
June 14, 2022Machine learning doesn’t have to be hard. Sure, it requires the ability to do some coding and the intuition for when, why, and how to apply certain models, but anyone can get started today with the learning resources and statistical packages freely available.
If you want to better understand what machine learning (ML) is and what it isn’t, join us for a series of free ML workshops hosted on the first Saturday of each month beginning 2 July 2022 at 2pm EDT.
Each session will focus on real-world machine learning coding techniques using Python and Scikit-learn.
Why Python?
Python is the most widely-used data science programming language of the day. It is used to support a variety of applications, is situated perfectly for web development, and plays well with big data through specialized packages like PySpark.
Why Scikit-learn?
Conducting machine learning projects used to require standalone code or packages for implementing specific models. This made it difficult to bounce around and quickly experiment with alternative approaches. Data also had to pre-processed in certain formats and tested, trained, and evaluated with inconsistent steps.
Dedicated packages like Scikit-learn bring everything you need under one roof. More importantly, they bring consistency to the machine learning process. Scikit-learn is an easy-to-use package for building machine learning models in Python. It provides unmatched flexibility to experiment and learn.
6 Free DataKwery Workshops
DataKwery will host six workshops on Zoom to cover practical applications of regression and classification techniques. You can register for each session for by clicking the links below.
1. Building Your First Regression Model in Python with Scikit-learn Recording now available
2. Feature Engineering Foundations in Python with scikit-learn Recording now available
3. Evaluating and Fine-Tuning Regression Models in Python with scikit-learn Recording now available
4. Building Your First Classification Model in Python with scikit-learnRecording now available
5. Evaluating and Fine-Tuning Classification Models in Python with scikit-learnRecording now available
How much does it cost?
It is completely free. Alex and David, co-founders of DataKwery, are building a new curriculum and welcome you to try it with us first.
What software do I need?
You can either code along in real-time or absorb what we cover and then try it later on your own. We’ll provide you with all the data and code, which you’ll be able to run on your own machine or online for free with Deepnote.
Who should attend?
If you have basic python programming skills and are interested in learning more about applied machine learning, this workshop is for you. Sign up now to secure your free seat!