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Tag: Industryready
Modern Time Series Forecasting with Python: Explore industry-ready time series forecasting using modern machine learning and deep learning
Price: $52.99
(as of Dec 17,2024 04:57:33 UTC – Details)
Publisher : Packt Publishing (November 24, 2022)
Language : English
Paperback : 552 pages
ISBN-10 : 1803246804
ISBN-13 : 978-1803246802
Item Weight : 2.09 pounds
Dimensions : 9.25 x 7.52 x 1.14 inches
Time series forecasting is a powerful tool used in various industries to predict future trends and patterns based on historical data. In this post, we will explore how to perform industry-ready time series forecasting using modern machine learning and deep learning techniques in Python.Some of the key topics we will cover include:
1. Introduction to time series forecasting: We will discuss the importance of time series forecasting in different industries and applications.
2. Data preparation and preprocessing: We will walk through the process of preparing and preprocessing time series data for modeling.
3. Traditional time series forecasting models: We will cover popular traditional time series forecasting models such as ARIMA, SARIMA, and exponential smoothing.
4. Machine learning-based time series forecasting: We will explore how machine learning algorithms such as Random Forest, Gradient Boosting, and LSTM can be used for time series forecasting.
5. Hyperparameter tuning and model evaluation: We will discuss techniques for tuning hyperparameters and evaluating the performance of time series forecasting models.
6. Case study: We will work on a real-world case study to demonstrate how to apply modern time series forecasting techniques in practice.
By the end of this post, you will have a solid understanding of how to leverage modern machine learning and deep learning techniques for time series forecasting in Python. Whether you are a data scientist, analyst, or researcher, this post will equip you with the knowledge and skills to build accurate and reliable time series forecasting models for your industry-specific needs.
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Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas
Price:$57.99– $55.09
(as of Dec 15,2024 19:46:15 UTC – Details)
From the brand
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Our mission is to increase the shared value of deep tech knowledge by helping tech pros put software to work.
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ASIN : B0D6G3SHD6
Publisher : Packt Publishing; 2nd ed. edition (October 31, 2024)
Language : English
Paperback : 658 pages
ISBN-10 : 1835883184
ISBN-13 : 978-1835883181
Item Weight : 3.03 pounds
Dimensions : 1.41 x 7.5 x 9.25 inches
Time series forecasting is a crucial task in many industries, from finance to marketing to healthcare. With the advent of machine learning and deep learning, the field of time series forecasting has been revolutionized. In this post, we will explore how to perform industry-ready time series analysis using Python, PyTorch, and pandas.PyTorch is a popular deep learning library that provides a flexible and efficient platform for building and training neural networks. pandas is a powerful data manipulation library that is widely used for working with time series data. By combining these two libraries, we can create powerful and accurate time series forecasting models.
In this post, we will cover the following topics:
1. Preprocessing time series data using pandas
2. Building machine learning models for time series forecasting
3. Implementing deep learning models for time series forecasting with PyTorch
4. Evaluating the performance of time series forecasting models
5. Deploying industry-ready time series forecasting modelsBy the end of this post, you will have a solid understanding of how to leverage Python, PyTorch, and pandas to perform advanced time series forecasting for a wide range of industries. Stay tuned for our upcoming tutorials on this topic!
#Modern #Time #Series #Forecasting #Python #Industryready #machine #learning #deep #learning #time #series #analysis #PyTorch #pandas
