Machine Learning Strategies for Time Series Forecasting

  • 2019-02-21 06:45 AM
  • 1184

Zero to Deep Learning™ with Python and Keras ☞
Machine Learning and Deep Learning using Tensor Flow & Keras ☞
Deep Learning Prerequisites: Logistic Regression in Python ☞

Forecasting time-series data has applications in many fields, including finance, health, etc. There are potential pitfalls when applying classic statistical and machine learning methods to time-series problems. This talk will give folks the basic toolbox to analyze time-series data and perform forecasting using statistical and machine learning models, as well as interpret and convey the outputs.

PyData is an educational program of NumFOCUS, a 501©3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

Social Network for Developers ☞
Developers Chat Channel ☞
Learn to code for free and get a developer job ☞