| 1. About this Course.mp4 | 33.4 MB | ||
| 1. About this Course.srt | 4.8 KB | ||
| 1. Anomaly Detect & Forecasting Project Overview.mp4 | 56 MB | ||
| 1. Anomaly Detect & Forecasting Project Overview.srt | 7.7 KB | ||
| 1. Anomaly Detection.mp4 | 119.8 MB | ||
| 1. Anomaly Detection.srt | 16.1 KB | ||
| 1. Autocorrelation.mp4 | 48.8 MB | ||
| 1. Autocorrelation.srt | 9 KB | ||
| 1. Classification Project Overview.mp4 | 63.7 MB | ||
| 1. Classification Project Overview.srt | 9.1 KB | ||
| 1. Dashboard Project Overview.mp4 | 69.8 MB | ||
| 1. Dashboard Project Overview.srt | 11.3 KB | ||
| 1. Segmentation.mp4 | 62.6 MB | ||
| 1. Segmentation.srt | 11.2 KB | ||
| 1. Sequence Prediction Project Overview.mp4 | 107.4 MB | ||
| 1. Sequence Prediction Project Overview.srt | 19.2 KB | ||
| 1. Signal Processing Project Overview.mp4 | 147 MB | ||
| 1. Signal Processing Project Overview.srt | 13.8 KB | ||
| 1. Time Series Segmentation Project.mp4 | 113.5 MB | ||
| 1. Time Series Segmentation Project.srt | 13.9 KB | ||
| 1. Waves and Signals.mp4 | 44.1 MB | ||
| 1. Waves and Signals.srt | 5.7 KB | ||
| 1. What Else is There to Know About Time Series.mp4 | 29.7 MB | ||
| 1. What Else is There to Know About Time Series.srt | 3.6 KB | ||
| 1.1 Code on GitHub.html | 102.4 B | ||
| 1.1 Code on Kaggle.html | 102.4 B | ||
| 1.1 Code repository for the projects in this course..html | 102.4 B | ||
| 1.1 Dataset Source.html | 102.4 B | ||
| 1.1 ECG Dataset from Kaggle.html | 102.4 B | ||
| 1.1 Graph of sine and cosine functions on Desmos.html | 102.4 B | ||
| 1.1 Jason Brownlee's Book.html | 102.4 B | ||
| 1.1 Maestro MIDI Dataset.html | 102.4 B | ||
| 1.2 Code on GitHub.html | 102.4 B | ||
| 1.2 Data Science in Layman's Terms Statistics.html | 102.4 B | ||
| 1.2 LIGO's Webiste.html | 102.4 B | ||
| 1.2 Paper that Describes the Dataset and How it Was Processed.html | 102.4 B | ||
| 1.2 San Francisco Police Districts GeoJSON.html | 102.4 B | ||
| 1.3 Code on GitHub.html | 102.4 B | ||
| 1.3 Quantstart Advanced Algorithmic Trading.html | 102.4 B | ||
| 1.3 San Francisco Crime Data 2003-2018.html | 204.8 B | ||
| 1.4 R Package for Benford's Law.html | 102.4 B | ||
| 1.4 San Francisco Crime Data 2018-Present.html | 204.8 B | ||
| 1.4 YouTube Video that Plays the Event as a .wav File.html | 102.4 B | ||
| 2. Anomaly Detection Quiz.html | 102.4 B | ||
| 2. Dashboard Project Code.mp4 | 499.6 MB | ||
| 2. Dashboard Project Code.srt | 38.2 KB | ||
| 2. Data Exploration and Cleaning.mp4 | 252.1 MB | ||
| 2. Data Exploration and Cleaning.srt | 27.4 KB | ||
| 2. Forecasting with Constant Variance.mp4 | 140.3 MB | ||
| 2. Forecasting with Constant Variance.srt | 21.5 KB | ||
| 2. Music Generation main.py.mp4 | 66.4 MB | ||
| 2. Music Generation main.py.srt | 8.9 KB | ||
| 2. Segmentation Quiz.html | 102.4 B | ||
| 2. Signal Processing Code.mp4 | 162 MB | ||
| 2. Signal Processing Code.srt | 17.7 KB | ||
| 2. The Fourier Transform.mp4 | 163.8 MB | ||
| 2. The Fourier Transform.srt | 13.4 KB | ||
| 2. Time Series Overview.mp4 | 43 MB | ||
| 2. Time Series Overview.srt | 6.1 KB | ||
| 2. Writing a Data Processor Script.mp4 | 93.8 MB | ||
| 2. Writing a Data Processor Script.srt | 12.8 KB | ||
| 2.1 Supplementary video explanation of the Fourier Transform.html | 102.4 B | ||
| 3. Building the Classification Models.mp4 | 129.6 MB | ||
| 3. Building the Classification Models.srt | 17.1 KB | ||
| 3. Feature Engineering and Visualization.mp4 | 290.1 MB | ||
| 3. Feature Engineering and Visualization.srt | 28.6 KB | ||
| 3. Filters and Wavelets.mp4 | 67 MB | ||
| 3. Filters and Wavelets.srt | 10.2 KB | ||
| 3. Forecasting with Non-Constant Variance.mp4 | 58.3 MB | ||
| 3. Forecasting with Non-Constant Variance.srt | 9.4 KB | ||
| 3. Music Generation Pre-Processing.mp4 | 200.1 MB | ||
| 3. Music Generation Pre-Processing.srt | 28.3 KB | ||
| 4. Anomaly Detection and Forecasting Model.mp4 | 136.2 MB | ||
| 4. Anomaly Detection and Forecasting Model.srt | 14.7 KB | ||
| 4. Evaluating the Classification Models.mp4 | 68.4 MB | ||
| 4. Evaluating the Classification Models.srt | 11 KB | ||
| 4. Forecasting with Nonlinear Models.mp4 | 158.8 MB | ||
| 4. Forecasting with Nonlinear Models.srt | 22.7 KB | ||
| 4. Music Generation Model.mp4 | 267.8 MB | ||
| 4. Music Generation Model.srt | 35.3 KB | ||
| 4. Signal Processing Quiz.html | 102.4 B | ||
| 4.1 Cross validation for time series example.html | 102.4 B | ||
| 4.2 Facebook Prophet.html | 102.4 B | ||
| 5. Deploying the Models to an API.mp4 | 37 MB | ||
| 5. Deploying the Models to an API.srt | 6.1 KB | ||
| 5. Forecasting with Neural Networks.mp4 | 186.5 MB | ||
| 5. Forecasting with Neural Networks.srt | 25.6 KB | ||
| 5. Music Generation Output.mp4 | 65 MB | ||
| 5. Music Generation Output.srt | 7.7 KB | ||
| 5.1 Convolutional layers learn different levels of features in different layers.html | 102.4 B | ||
| 5.1 Listen to a MIDI file..html | 102.4 B | ||
| 5.2 The paper that introduced the transformer Attention is All You Need.html | 102.4 B | ||
| 6. Forecasting Quiz.html | 102.4 B | ||
| Bonus Resources.txt | 307.2 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 97 total files | |||
Data Science in Layman's Terms: Time Series Analysis
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz
Language: English | Size: 3.88 GB | Duration: 7h 35m
Modeling Time Series Data
What you'll learn
Time series forecasting with modern nonlinear models, neural networks, and AI
Time series classification, with a project on predicting heart attackes from ECG data
Time series segmentation, with a project categorizing distinct periods of football QB performance
Signal processing, with a project detecting gravitational waves hidden amongst noise
Anomaly detection, with a project detecting faulty inverters at solar power plants
Geospatial-temporal analysis, with a project creating a dashboard to analyze crime in San Francisco
How to build a dashboard with Dash and Plotly
How to deploy machine learning as a service (MLaaS), using an API
How to generate music with AI
How to build & utilize custom neural networks for time series, including LSTMs and Transformers
Description
This course explores a specific domain of data science: time series analysis. The lectures explain topics in time series from a high level perspective, so that you can get a logical understanding of the concepts without getting intimidated by the math or programming. Whether you are new to time series or an experienced data scientist, this course covers every aspect of time series. Topics in time series analysis include:
Forecasting - Predicting the future
Classification - Categorize a series
If You Need More Courses, kindly Visit and Support Us -->> https://FreeCourseWeb.com
Thank You.
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