protonAutoML
@protonAutoML
Analytics for your Organization without Code or Data Science background
قد يعجبك
Machine Learning Strategy when there is no data #cartoon buff.ly/3jbXOEf
web-based e-mail assistant to send follow-up e-mails to a list of e-mail subscribers; it’s quite another to apply AI technology to such tasks as how to fill out a tax form or what websites should get the most traffic. #MachineLearning #AI
first time, like playing a video game, rather than performing a repeatable task.) AI tools typically recognize patterns in digital data, sift through the patterns, and then decide how best to apply them to decision making in real-time. It’s one thing to use a digital query or
Artificial intelligence” has been around for a long time, but it’s usually used to describe how a machine performs a specific task on its own rather than something it does for the first time. (Google’s DeepMind computer is an example of an AI system that performs a task for the
When someone said their machine learning model gets 100% accuracy.
Answer to What are some screenshots which deserve 10k upvotes? by @protonAutoML quora.com/What-are-some-…
IoT, AI, analytics and telematics can help small businesses improve their efficiency and bottom line tek.io/2T9YTD7
Not every problem should be solved using machine learning. Unless you have a pretrained model.
Say, you own a clothing outlet. A customer purchases clothes from you for 20 years and spends $50 every year. So, his customer lifetime value will be $100 ($50 X 20), minus all the resources you spent to acquire this customer.
Customer Lifetime Value (CLV) CLV is the estimate of the financial worth a business acquires from their entire relationship with a customer. In short, the sum of returns the company gets over the “life” of a customer. Let us explain you CLV using a simple example.
designing profitable marketing campaigns after understanding the customer’s desires and pain points. All the data collected from the internet about customers can be used to run personalized marketing campaigns that have higher returns on investment.
product on any e-commerce site, you will find ads of that product everywhere you go online. While some people have raised privacy concerns over this, it’s not always a bad thing. Big data has the potential of being the most promising tool in marketing. Marketing is about
Whenever you are on the internet, every link you click on, all the sites you visit, all the things you search about, all the cookies saved in your browser - all this information about you gets stored in the form of big data. That’s why when you search for something or check out a
sentiment analysis software like ProtonAutoML More on this here - protonautoml.com/post/want-to-i… #ml #ai #DataScience
customers, and making product improvements. Monitoring reviews has become increasingly important as more consumers, especially younger ones, rely on them for purchase decisions. Staying abreast of what customers are saying online is a complex task that’s made simpler by
Sentiment analysis allows brands to stay on top of consumer opinion and intervene where possible. For example, by monitoring reviews of their business(es) and products, brands can take actions such as addressing negative reviews online, reaching out directly to dissatisfied
linguistics to data-mine sources like social media comments, blogs, and product reviews for relevant input. This input is typically scored as positive, neutral, or negative and made available through reporting tools.
United States الاتجاهات
- 1. Chiefs 76.2K posts
- 2. Broncos 53.8K posts
- 3. Shedeur 39.4K posts
- 4. Browns 43.4K posts
- 5. Ravens 44.5K posts
- 6. Mahomes 20.7K posts
- 7. Rams 26.6K posts
- 8. Bo Nix 10.5K posts
- 9. Gabriel 64.1K posts
- 10. Sam Darnold 11.2K posts
- 11. #FlyEaglesFly 8,818 posts
- 12. Lions 45.6K posts
- 13. Seahawks 25.4K posts
- 14. Lamar 20.1K posts
- 15. Goff 3,499 posts
- 16. Riley Moss 3,979 posts
- 17. Lane Johnson N/A
- 18. Jordan Davis N/A
- 19. Kevin Patullo 1,126 posts
- 20. Myles Garrett 6,803 posts
Something went wrong.
Something went wrong.