Business Intelligence and Analytics - RNN for Time Series Forecasts

Master Data Mastery: Transform, Analyze, and Visualize! Dive into the world of Big Data, Governance, Python Analytics, Machine Learning, and AI with Stephanie Powers. Unlock data's power and elevate your expertise in modern analytics and data engineering. Enroll now!

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What you'll learn

Understand and apply data governance principles to manage data effectively.
Analyze data types and structures using Python for data engineering tasks.
Create dashboards and visualizations in Python to present analytical insights.
Implement machine learning models in Python for classification and prediction tasks.

This course includes

56.5 hours of video
Certificate of completion
Access on mobile and TV

Business Intelligence and Analytics RNN for Time Series Forecasts

RNN for Time Series Forecasts Transcript and Lesson Notes

Using LSTM and Recurrent Neural Networks to forecast time series data, such as stock prices. Python workbook available here: https://drstephpowers.github.io/BIA/

Quick Summary

Using LSTM and Recurrent Neural Networks to forecast time series data, such as stock prices. Python workbook available here: https://drstephpowers.github.io/BIA/

Key Takeaways

Review the core idea: Using LSTM and Recurrent Neural Networks to forecast time series data, such as stock prices. Python workbook available here: https://drstephpowers.github.io/BIA/
Understand how time fits into RNN for Time Series Forecasts.
Understand how series fits into RNN for Time Series Forecasts.
Understand how forecasts fits into RNN for Time Series Forecasts.
Understand how business fits into RNN for Time Series Forecasts.

Key Concepts

time series forecasts business intelligence analytics React Laravel Machine Learning Docker Python JavaScript TypeScript PHP API SQL MySQL PostgreSQL CSS HTML

Full Transcript

Using LSTM and Recurrent Neural Networks to forecast time series data, such as stock prices. Python workbook available here: https://drstephpowers.github.io/BIA/

Lesson FAQs

What is RNN for Time Series Forecasts about?

Using LSTM and Recurrent Neural Networks to forecast time series data, such as stock prices. Python workbook available here: https://drstephpowers.github.io/BIA/

What key concepts are covered in this lesson?

The lesson covers time, series, forecasts, business, intelligence.

What should I learn before RNN for Time Series Forecasts?

Review the previous lessons in Business Intelligence and Analytics, then use the transcript and key concepts on this page to fill any gaps.

How can I practice after this lesson?

Practice by applying the main concepts: time, series, forecasts, business.

Does this lesson include a transcript?

Yes. The full transcript is visible on this page in indexable HTML sections.

Is this lesson free?

Yes. CourseHive lessons and courses are available to learn online for free.