Forecasting 📈 is perhaps the most common application of machine learning in the real world. Time series forecasting is a broad field with a long history. This course focuses on the application of modern machine learning methods to time series data with the goal of producing the most accurate predictions. The lessons in this course were inspired by winning solutions from past Kaggle forecasting competitions but will be applicable whenever accurate forecasts are a priority.
After finishing this course, you'll know how to:
As part of the exercises, you'll get a chance to participate in our Store Sales - Time Series Forecasting Getting Started competition. In this competition, you're tasked with forecasting sales for Corporación Favorita (a large Ecuadorian-based grocery retailer) in almost 1800 product categories.
To check the learning material in advance, check Kaggle's microcourse 👇 :
https://www.kaggle.com/learn/time-series
Let's get started!
Prerequisites:
1. Have access to a Browser (preferably Google Chrome)
2. Sign up to Kaggle
3. Eager to Learn !!!
4.Have Completed the courses:
GDG Cloud Edmonton | WTM Ambassador
Data Analyst
Vector Institute AI Scholarship Recipient
ML Researcher with a focus in Medical Imaging(CV) and NLP
Vannia is a promising data scientist, based in Edmonton, Canada. She has work on projects which combines time series analysis and machine learning. Her passion for coding took her to the Data Science field and Web Development. She is leads GDG Cloud Edmonton, where she loves to help their community upgrade their skills as she did in her beginnings. She enjoys working out outdoors, binging a Netflix series, and replicating authentic Mexican food in her spare time. Above all, she wants to empower adult women, especially family women, to transition to Tech.
Devipriya Raju is a first-year graduate student at the University of Alberta, holding a master's degree in data science from the University of Wisconsin. Her research focuses primarily on Deep Learning in the domain of Medical Imaging. She is proficient in Tensorflow, Pytorch, Scikit-Learn, Scipy, and OpenCV. With three years of industry experience in Python and R programming, she has gained valuable expertise in implementing cutting-edge methodologies. Her research interests include the detection of Alzheimer's, breast cancer analysis on fMRI images, and the classification of bird species based on their distinct bird sounds. During her leisure time, she enjoys hiking and capturing the beauty of nature through her lens.
Government of Alberta
GDG organizer - WTM Ambassador - System Analyst -
Canadian Centre for Mapping and Earth Observation
GDG Organizer
Treasurer
Event & Technical
Softmax Data
Event & Technical
GDG Cloud Edmonton
Marketing
Volunteer
GDG Co-organizer
Volunteer
Technical
