About this video

Time Series Analysis allows us to analyze data that is generated over a period of time and has sequential interdependencies between the observations. This video describes special mathematical tricks and techniques that are geared towards exploring the internal structures of time series data and generating powerful descriptive and predictive insights. Also, the tutorial is full of real-life time series examples and their analyses using cutting-edge solutions developed in Python. The video starts with a descriptive analysis to create insightful visualizations of internal structures such as trend, seasonality, and autocorrelation. Next, the statistical methods of dealing with autocorrelation and non-stationary time series are described. This is followed by exponential smoothing to produce meaningful insights from noisy time series data. At this point, we shift the focus towards predictive analysis and introduce autoregressive models such as ARMA and ARIMA for time series forecasting. Later, powerful deep learning methods are presented to develop accurate forecasting models for complex time series. All the topics are illustrated with real-life problem scenarios and their solutions by best-practice implementations in Python.

Style and Approach

This course takes viewers from basic to advanced time series analysis in a very practical way, and with real-world use cases.

Publication date:
December 2017
2 hours 25 minutes

About the Authors

  • Dr. Avishek Pal

    Dr. Avishek Pal, PhD, is a software engineer, data scientist, author, and an avid Kaggler living in Hyderabad, India. He achieved his Bachelor of Technology degree in industrial engineering from the Indian Institute of Technology (IIT) Kharagpur and earned his doctorate in 2015 from University of Warwick, Coventry, United Kingdom.

    He started his career as a software engineer at IBM India developing middleware solutions for telecom clients. This was followed by stints at a start-up product development company followed by Ericsson, the global telecom giant.

    After doctoral studies, Avishek started his career in India as a lead machine learning engineer for a leading US-based investment company. He is currently working at Microsoft as a senior data scientist.

    Avishek has published several research papers in reputed international conferences and journals.

    Browse publications by this author
  • Dr. PKS Prakash

    Dr. PKS Prakash is a data scientist and author.

    He has spent the last 12 years in developing many data science solutions in several practical areas in healthcare, manufacturing, pharmaceuticals, and e-commerce. He currently works as the data science manager at ZS Associates. He is the co-founder of Warwick Analytics, a spin-off from University of Warwick, UK. Prakash has published articles widely in research areas of operational research and management, soft computing tools, and advanced algorithms in leading journals such as IEEE-Trans, EJOR, and IJPR, among others. He has edited an article on Intelligent Approaches to Complex Systems and contributed to books such as Evolutionary Computing in Advanced Manufacturing published by WILEY and Algorithms and Data Structures using R and R Deep Learning Cookbook, published by PACKT.

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Latest Reviews

(4 reviews total)
Video is a walk-through of the textbook examples, not much use in isolation but helpful when used with the book.
Awesome deal on quite a few quality textbooks and lectures! Well worth the money, contains quality literature that's very helpful and easy to read.
The course is taught very mechanic. This course is not helpful either you don't know machine learning & its algorithms or python. In the end, you learn nothing! Neither you python knowledge is improved, neither you learn any machine learning algorithm. There are very few comparisons of different algorithms and the reasoning behind them and when you choose one instead of another.

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