Your cart is currently empty!
Tag: Forecasting
Deep Learning for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detection
Price:$49.99– $47.42
(as of Dec 13,2024 19:50:39 UTC – Details)
From the brand
See more at our store:
Packt is a leading publisher of technical learning content with the ability to publish books on emerging tech faster than any other.
Our mission is to increase the shared value of deep tech knowledge by helping tech pros put software to work.
We help the most interesting minds and ground-breaking creators on the planet distill and share the working knowledge of their peers.
Publisher : Packt Publishing (March 29, 2024)
Language : English
Paperback : 274 pages
ISBN-10 : 1805129236
ISBN-13 : 978-1805129233
Item Weight : 1.05 pounds
Dimensions : 7.5 x 0.58 x 9.25 inches
Deep Learning for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detectionAre you looking to dive deep into the world of time series analysis using deep learning techniques? Look no further than our latest cookbook, which is packed with practical recipes for using PyTorch and Python to tackle time series forecasting, classification, and anomaly detection.
In this cookbook, you will find step-by-step instructions for building and training deep learning models for time series data. From preprocessing and feature engineering to model evaluation and deployment, each recipe is designed to help you master the art of time series analysis with PyTorch.
Whether you are a beginner looking to get started with time series analysis or an experienced data scientist seeking to expand your skill set, this cookbook has something for everyone. With a focus on real-world applications and hands-on exercises, you will learn how to leverage the power of deep learning to extract valuable insights from time series data.
So why wait? Pick up a copy of our Deep Learning for Time Series Cookbook today and start building your own cutting-edge time series models with PyTorch and Python. Happy coding!
#Deep #Learning #Time #Series #Cookbook #PyTorch #Python #recipes #forecasting #classification #anomaly #detection
La Crosse Technology Professional Smart Wi-Fi Weather Station with Remote Monitoring (400 Foot Range), Wind and Rain Gauges, Temperature and Humidity Sensors, and Forecasting – V42-PRO-INT
Price:$159.95– $144.49
(as of Dec 02,2024 17:06:20 UTC – Details)
The Wireless Professional Weather Station from La Crosse Technology offers all the weather information you need to make sure Mother Nature’s unpredictability does not ruin your day. The dynamic color forecast icons, with changing seasonal foliage, shows what the weather is going to be like for the day. Along with your personal, up-to-the-minute wind, rain and indoor/outdoor temperature and humidity, you know what is happening inside and outside your home, providing you the information to make the decision to adjust your thermostat, wear your jacket or even monitor rainfall to know when it is necessary to water your lawn. When choosing to use the connectable feature, you now open your station to the enhanced features, which includes data streaming weather information providing your station with more detailed forecast information including the Hi’s and Lo’s for the day, chance of precipitation, as well as 8 additional forecast icons to keep you up to date to the weather to come.
MONITOR YOUR HOME’S WEATHER ON EASY-TO-READ DISPLAY – DYNAMIC FORECAST with Vibrant color icons: 6 different views as StandAlone Station (EXTENDABLE VIEWS – when connected to Wi-Fi) and Seasonal Foliage scene changes
VIEW TODAY’S FUTURE FORECAST, plus next 7 days; WITH EXTENDED WI-FI CONNECTION, view the upcoming week’s forecast data and toggle through the next 12 hours with the Press of a Button; Enhanced background forecasting scenes when Wi-Fi connected
WIND DATA and RAINFALL MEASUREMENTS – View current & top speed, with direction and compass rose; Rain graph and historical records with Auto-scroll option; Indoor and Outdoor Temperature (°F/°C) with Humidity readings; Set Custom Alerts; Records HI/LO values with time and date stamp; Indoor comfort meter
ENHANCED data when Wi-Fi connected, including: AccuWeather data streaming options, UV index, sunrise/set times, thunderstorms, air quality and more; Track and Monitor your Home’s Backyard Weather on free La Crosse View mobile app with customizable Alerts & Notifications
Outdoor Temperature Range: -40°F to 140°F (-40°C to 60°C) with Transmission Range: Up to 400 ft; Battery operation (Station: includes 5V adapter and CR2032 battery back-up (battery retains data, does not run system); Includes LTV-TH5i Temperature/Humidity Sensor requires 2 AA batteries (not included) and LTV-WSDR1 Wind/Rain sensor requires 3 AA batteriesCustomers say
Customers like the ease of setup of the weather station. They mention it’s lightweight, easy to access, and correctly installed. However, some customers have reported issues with WiFi connectivity. Opinions differ on functionality, accuracy, display quality, and value for money.
AI-generated from the text of customer reviews
Are you looking for a top-of-the-line weather station that offers advanced features and remote monitoring capabilities? Look no further than the La Crosse Technology Professional Smart Wi-Fi Weather Station with Remote Monitoring (400 Foot Range), Wind and Rain Gauges, Temperature and Humidity Sensors, and Forecasting – V42-PRO-INT.This weather station is perfect for weather enthusiasts, gardeners, farmers, and anyone who wants to stay informed about local weather conditions. With a 400-foot range, you can conveniently monitor the weather from inside your home or office. The wind and rain gauges provide accurate measurements of wind speed and precipitation, while the temperature and humidity sensors keep you informed about current conditions.
The forecasting feature allows you to plan your day with confidence, knowing what weather to expect. Plus, the remote monitoring capabilities allow you to access real-time weather data from anywhere using your smartphone or computer.
Don’t settle for a basic weather station when you can have the La Crosse Technology Professional Smart Wi-Fi Weather Station with Remote Monitoring (400 Foot Range), Wind and Rain Gauges, Temperature and Humidity Sensors, and Forecasting – V42-PRO-INT. Stay ahead of the weather and make informed decisions with this high-quality weather station.
#Crosse #Technology #Professional #Smart #WiFi #Weather #Station #Remote #Monitoring #Foot #Range #Wind #Rain #Gauges #Temperature #Humidity #Sensors #Forecasting #V42PROINT
Utilizing SAS for Predictive Modeling and Forecasting
In today’s data-driven world, businesses are constantly seeking ways to gain a competitive edge by leveraging the power of predictive modeling and forecasting. One of the most widely used tools for this purpose is SAS, a powerful software suite that offers a wide range of capabilities for analyzing and interpreting data.Utilizing SAS for predictive modeling and forecasting allows businesses to make more informed decisions based on historical data trends and patterns. By analyzing past data, businesses can identify potential future outcomes and trends, enabling them to anticipate changes in the market and make strategic decisions that will drive growth and success.
One of the key features of SAS is its ability to handle large volumes of data, making it ideal for businesses with complex datasets. SAS offers a variety of statistical tools and techniques that can be used to build predictive models, including regression analysis, decision trees, and neural networks. These models can be used to forecast future trends, identify patterns, and detect anomalies in the data.
In addition to its modeling capabilities, SAS also offers advanced visualization tools that allow users to easily interpret and communicate their findings. By visualizing data in charts, graphs, and dashboards, businesses can quickly identify important trends and patterns, and communicate their findings to stakeholders in a clear and concise manner.
Furthermore, SAS offers a range of forecasting techniques that can help businesses predict future outcomes based on historical data. By utilizing time series analysis, businesses can forecast future sales, demand, and other key metrics, enabling them to make more accurate predictions and optimize their operations.
Overall, utilizing SAS for predictive modeling and forecasting can provide businesses with a competitive advantage by enabling them to make data-driven decisions that drive growth and success. With its powerful capabilities and user-friendly interface, SAS is a valuable tool for businesses looking to harness the power of data to drive business outcomes.
Data Science for Supply Chain Forecasting
Price:$54.99– $41.99
(as of Nov 25,2024 14:43:46 UTC – Details)
Publisher : De Gruyter; 2nd ed. edition (March 22, 2021)
Language : English
Perfect Paperback : 310 pages
ISBN-10 : 3110671107
ISBN-13 : 978-3110671100
Item Weight : 1.16 pounds
Dimensions : 9.5 x 0.7 x 6.6 inches
Data Science has revolutionized the way companies forecast demand, manage inventory, and optimize their supply chains. By leveraging advanced analytics, machine learning, and artificial intelligence, businesses can gain valuable insights into consumer behavior, market trends, and operational efficiencies.In the realm of supply chain forecasting, data science plays a crucial role in improving accuracy, reducing costs, and enhancing overall performance. By analyzing historical sales data, weather patterns, economic indicators, and other relevant variables, companies can predict future demand with greater precision and make informed decisions about production, distribution, and inventory levels.
One of the key benefits of using data science for supply chain forecasting is the ability to detect patterns and trends that are not readily apparent to human analysts. By applying sophisticated algorithms to large datasets, businesses can uncover hidden relationships and correlations that can help them anticipate fluctuations in demand, identify potential bottlenecks in their operations, and proactively address supply chain disruptions.
Furthermore, data science enables companies to build predictive models that can forecast demand at different levels of granularity, from individual SKUs to product categories, regions, and time periods. These models can be continuously refined and updated based on new data, leading to more accurate and reliable forecasts that drive better decision-making and improved performance.
In conclusion, data science offers tremendous opportunities for enhancing supply chain forecasting and optimizing operations. By harnessing the power of advanced analytics and machine learning, businesses can gain a competitive edge in today’s fast-paced and dynamic marketplace. Embracing data science is essential for companies looking to stay ahead of the curve and achieve sustainable growth in the ever-evolving world of supply chain management.
#Data #Science #Supply #Chain #Forecasting
Capacity Forecasting: Anticipating Needs and Planning for the Future
In today’s fast-paced business environment, it is crucial for organizations to accurately forecast their capacity needs in order to effectively plan for the future. Capacity forecasting is the process of predicting the demand for a product or service and determining the resources needed to meet that demand. By anticipating future needs, companies can make informed decisions about staffing, production levels, and investment in infrastructure.One of the key benefits of capacity forecasting is that it allows organizations to avoid under- or over-utilization of resources. Underestimating capacity needs can result in missed opportunities and dissatisfied customers, while overestimating can lead to wasted resources and increased costs. By accurately predicting demand, companies can optimize their operations and ensure that they are able to meet customer expectations.
There are several methods that organizations can use to forecast capacity needs. One common approach is trend analysis, which involves examining historical data to identify patterns and trends that can be used to predict future demand. Another method is simulation modeling, which uses computer software to simulate different scenarios and determine the impact on capacity requirements.
In addition to these quantitative methods, organizations can also benefit from qualitative input from employees, customers, and industry experts. By gathering insights from multiple sources, companies can develop a more comprehensive understanding of the factors that may impact capacity needs in the future.
Capacity forecasting is particularly important for industries that experience fluctuating demand, such as retail, hospitality, and healthcare. In these sectors, accurate forecasting can help companies adjust staffing levels, inventory levels, and production schedules to meet changing demand.
Overall, capacity forecasting is a critical aspect of effective business planning. By anticipating future needs and planning accordingly, organizations can ensure that they have the resources in place to meet customer demand and achieve their strategic goals. By investing in capacity forecasting tools and processes, companies can position themselves for long-term success in a competitive marketplace.
