Download [ FreeCourseWeb ] Udemy - Data Science in Layman's Terms - Time Series Analysis torrent

[ FreeCourseWeb ] Udemy - Data Science in Layman's Terms - Time Series Analysis

Torrent:	[ FreeCourseWeb ] Udemy - Data Science in Layman's Terms - Time Series Analysis
Description:	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.
Downloads:	91
Category:	Other /Tutorials
Size:	3.9 GB
Show Files »	[ FreeCourseWeb.com ] Udemy - Data Science in Layman's Terms - Time Series Analysis Get Bonus Downloads Here.url (0.2 KB) ~Get Your Files Here ! 1. Introduction 1. About this Course.mp4 (33.4 MB) 1. About this Course.srt (4.8 KB) 1.1 Code repository for the projects in this course..html (0.1 KB) 2. Time Series Overview.mp4 (43.0 MB) 2. Time Series Overview.srt (6.1 KB) 10. Project Signal Processing 1. Signal Processing Project Overview.mp4 (147.0 MB) 1. Signal Processing Project Overview.srt (13.8 KB) 1.1 Dataset Source.html (0.1 KB) 1.2 LIGO's Webiste.html (0.1 KB) 1.3 Code on GitHub.html (0.1 KB) 1.4 YouTube Video that Plays the Event as a .wav File.html (0.1 KB) 2. Signal Processing Code.mp4 (162.0 MB) 2. Signal Processing Code.srt (17.7 KB) 11. Project Dashboard Building with Geospatial-Temporal Analysis 1. Dashboard Project Overview.mp4 (69.8 MB) 1. Dashboard Project Overview.srt (11.3 KB) 1.1 Code on GitHub.html (0.1 KB) 1.2 San Francisco Police Districts GeoJSON.html (0.1 KB) 1.3 San Francisco Crime Data 2003-2018.html (0.2 KB) 1.4 San Francisco Crime Data 2018-Present.html (0.2 KB) 2. Dashboard Project Code.mp4 (499.6 MB) 2. Dashboard Project Code.srt (38.2 KB) 12. Course Conclusion 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 Jason Brownlee's Book.html (0.1 KB) 1.2 Data Science in Layman's Terms Statistics.html (0.1 KB) 1.3 Quantstart Advanced Algorithmic Trading.html (0.1 KB) 1.4 R Package for Benford's Law.html (0.1 KB) 2. Time Series Forecasting 1. Autocorrelation.mp4 (48.8 MB) 1. Autocorrelation.srt (9.0 KB) 1.1 Graph of sine and cosine functions on Desmos.html (0.1 KB) 2. Forecasting with Constant Variance.mp4 (140.3 MB) 2. Forecasting with Constant Variance.srt (21.5 KB) 3. Forecasting with Non-Constant Variance.mp4 (58.3 MB) 3. Forecasting with Non-Constant Variance.srt (9.4 KB) 4. Forecasting with Nonlinear Models.mp4 (158.8 MB) 4. Forecasting with Nonlinear Models.srt (22.7 KB) 4.1 Cross validation for time series example.html (0.1 KB) 4.2 Facebook Prophet.html (0.1 KB) 5. Forecasting with Neural Networks.mp4 (186.5 MB) 5. Forecasting with Neural Networks.srt (25.6 KB) 5.1 Convolutional layers learn different levels of features in different layers.html (0.1 KB) 5.2 The paper that introduced the transformer Attention is All You Need.html (0.1 KB) 6. Forecasting Quiz.html (0.1 KB) 3. Anomaly Detection 1. Anomaly Detection.mp4 (119.8 MB) 1. Anomaly Detection.srt (16.1 KB) 2. Anomaly Detection Quiz.html (0.1 KB) 4. Segmentation 1. Segmentation.mp4 (62.6 MB) 1. Segmentation.srt (11.2 KB) 2. Segmentation Quiz.html (0.1 KB) 5. Signal Processing 1. Waves and Signals.mp4 (44.1 MB) 1. Waves and Signals.srt (5.7 KB) 2. The Fourier Transform.mp4 (163.8 MB) 2. The Fourier Transform.srt (13.4 KB) 2.1 Supplementary video explanation of the Fourier Transform.html (0.1 KB) 3. Filters and Wavelets.mp4 (67.0 MB) 3. Filters and Wavelets.srt (10.2 KB) 4. Signal Processing Quiz.html (0.1 KB) 6. Project Anomaly Detection & Forecasting 1. Anomaly Detect & Forecasting Project Overview.mp4 (56.0 MB) 1. Anomaly Detect & Forecasting Project Overview.srt (7.7 KB) 1.1 Code on Kaggle.html (0.1 KB) 2. Data Exploration and Cleaning.mp4 (252.1 MB) 2. Data Exploration and Cleaning.srt (27.4 KB) 3. Feature Engineering and Visualization.mp4 (290.1 MB) 3. Feature Engineering and Visualization.srt (28.6 KB) 4. Anomaly Detection and Forecasting Model.mp4 (136.2 MB) 4. Anomaly Detection and Forecasting Model.srt (14.7 KB) 7. Project Segmentation 1. Time Series Segmentation Project.mp4 (113.5 MB) 1. Time Series Segmentation Project.srt (13.9 KB) 1.1 Code on Kaggle.html (0.1 KB) 8. Project Sequence Prediction 1. Sequence Prediction Project Overview.mp4 (107.4 MB) 1. Sequence Prediction Project Overview.srt (19.2 KB) 1.1 Maestro MIDI Dataset.html (0.1 KB) 1.2 Code on GitHub.html (0.1 KB) 2. Music Generation main.py.mp4 (66.4 MB) 2. Music Generation main.py.srt (8.9 KB) 3. Music Generation Pre-Processing.mp4 (200.1 MB) 3. Music Generation Pre-Processing.srt (28.3 KB) 4. Music Generation Model.mp4 (267.8 MB) 4. Music Generation Model.srt (35.3 KB) 5. Music Generation Output.mp4 (65.0 MB) 5. Music Generation Output.srt (7.7 KB) 5.1 Listen to a MIDI file..html (0.1 KB) 9. Project Deploy a Time Series Classifier to an API 1. Classification Project Overview.mp4 (63.7 MB) 1. Classification Project Overview.srt (9.1 KB) 1.1 ECG Dataset from Kaggle.html (0.1 KB) 1.2 Paper that Describes the Dataset and How it Was Processed.html (0.1 KB) 1.3 Code on GitHub.html (0.1 KB) 2. Writing a Data Processor Script.mp4 (93.8 MB) 2. Writing a Data Processor Script.srt (12.8 KB) 3. Building the Classification Models.mp4 (129.6 MB) 3. Building the Classification Models.srt (17.1 KB) 4. Evaluating the Classification Models.mp4 (68.4 MB) 4. Evaluating the Classification Models.srt (11.0 KB) 5. Deploying the Models to an API.mp4 (37.0 MB) 5. Deploying the Models to an API.srt (6.1 KB) Bonus Resources.txt (0.3 KB) files
Added:	2021-07-18 11:09:08
Language:	English
Peers:	Seeders : 18 , Leechers : 8
Release name:	[ FreeCourseWeb ] Udemy - Data Science in Layman's Terms - Time Series Analysis
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