Hands-on Time Series Analysis with Python: From Basics to Bleeding Edge Techniques
B V / PATEL Vishwas
Résumé
You'll begin by reviewing time series fundamentals, the structure of time series data, pre-processing, and how to craft the features through data wrangling. Next, you'll look at traditional time series techniques like ARMA, SARIMAX, VAR, and VARMA using trending framework like StatsModels and pmdarima.
The book also explains building classification models using sktime, and covers advanced deep learning-based techniques like ANN, CNN, RNN, LSTM, GRU and Autoencoder to solve time series problem using Tensorflow. It concludes by explaining the popular framework fbprophet for modeling time series analysis. After reading Hands -On Time Series Analysis with Python , you'll be able to apply these new techniques in industries, such as oil and gas, robotics, manufacturing, government, banking, retail, healthcare, and more.
What You'll Learn:
* Explains basics to advanced concepts of time series
* How to design, develop, train, and validate time-series methodologies
* What are smoothing, ARMA, ARIMA, SARIMA,SRIMAX, VAR, VARMA techniques in time series and how to optimally tune parameters to yield best results
* Learn how to leverage bleeding-edge techniques such as ANN, CNN, RNN, LSTM, GRU, Autoencoder to solve both Univariate and multivariate problems by using two types of data preparation methods for time series.
* Univariate and multivariate problem solving using fbprophet.
Who This Book Is For
Data scientists, data analysts, financial analysts, and stock market researchers
Chapter 1: Time Series and its Characteristics
Chapter 2: Data Wrangling and Preparation for Time Series
Chapter 3: Smoothing Methods
Chapter 4: Regression Extension Techniques for Time Series
Chapter 5: Bleeding Edge Techniques
Chapter 6: Bleeding Edge Techniques for Univariate Time Series
Chapter 7: Bleeding Edge Techniques for Multivariate Time Series
Chapter 8: Prophet
Ashish Patel is a Senior Data Scientist, AI researcher, and AI Consultant with over seven years of experience in the field of AI, Currently living in Ahmedabad(INDIA). He has a Master of Engineering Degree from Gujarat Technological University and his keen interest and ambition to research in the following domains such as (Machine Learning, Deep Learning, Time series, Natural Language Processing, Reinforcement Learning, Audio Analytics, Signal Processing, Sensor Technology, IoT, Computer Vision). He is currently working as Senior Data Scientist for Cynet infotech Pvt Ltd. He has published more than 15 + Research papers in the field of Data Science with Reputed Publications such as IEEE. He holds Rank 3 as a kernel master in Kaggle. Ashish has immense experience working on cross-domain projects involving a wide variety of data, platforms, and technologies
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Apress |
| Auteur(s) | B V / PATEL Vishwas |
| Parution | 24/08/2020 |
| Nb. de pages | 407 |
| EAN13 | 9781484259917 |
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