Machine Learning for Time Series Data in Python

Name: Machine Learning for Time Series Data in Python
Brand: Careervira
Price: 581 HKD
Availability: InStock
Rating: 1 (1 reviews)

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DataCamp

Course Report

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Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

Video Content

4 hours

Course Description

Time series data is ubiquitous. A time series is any signal that changes over time, such as stock market fluctuations or data about climate change. Machine learning can be used to harness the complexity of data and create predictions. This course brings together the worlds of machine learning and time series data. This course covers features engineering, machine learning and spectograms.

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Case Studies, Captstone Projects

Skills You Will Gain

Prerequisites/Requirements

Supervised Learning with scikit-learn

Visualizing Time Series Data in Python

Manipulating Time Series Data in Python

What You Will Learn

This course focuses on feature engineering and machine learning for time series data

This course is an intersection between these two worlds of machine learning and time series data, and covers feature engineering, spectograms, and other advanced techniques in order to classify heartbeat sounds and predict stock prices

Course Content

Expand all sections

Module 1: Time Series and Machine Learning Primer

Module 2: Time Series as Inputs to a Model

Module 3: Predicting Time Series Data

Module 4: Validating and Inspecting Time Series Models

Course Instructors

Chris Holdgraf

Fellow at the Berkeley Institute for Data Science

Chris Holdgraf is a fellow at the Berkeley Institute for Data Science at UC Berkeley. He has a PhD in cognitive neuroscience from UC Berkeley. His work is at the boundary between technology, open-sou...