Delta Sales App is a sales tracking software for field sales automation & employee location tracking to automate company sales and outside field sales activities with ease. This software is designed and developed for sales managers, distributors, brands to manage field sales forces activities. With the use of Delta Sales App, brands, distributors, sales managers can manage field sales employee activities and track their geo-location whereas field sales representatives having Delta Sales App installed in their handsets can automate their routine activities like order taking, payment collections, attendance making, applying for leave, expense management, and more.
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We can track the live location of the sales field person. The orders are also easy to enter as it saves a lot of time. The feature of dispatch is also easy to use and with the help of few clicks we can perform the sales related activities.
I was really having a problem keeping the party's details up to date and communicating to all the employees. All this was taking down the sales of the company and I was unable to hold everything at a balance. I thought about giving a try to the Delta sales app as it consists of almost every feature which I needed at that point in time. I implemented the app in my company and as expected delta sales app turned to be super helpful to my company.
Delta Sales APP that can be utilized by salespeople at any time and in any location with proper order, collection and complete report.
Based on our record, Scikit-learn seems to be a lot more popular than DeltaSalesApp. While we know about 29 links to Scikit-learn, we've tracked only 1 mention of DeltaSalesApp. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Delta Sales Appis a user-friendly cloud-based field sales tracking software that helps in managing sales of your business. Source: about 1 year ago
How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 18 days ago
Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 4 months ago
Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / about 1 year ago
The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: about 1 year ago
Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago
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