A magical solution that is not a school problem The unified policy of schools is often referred to as Band-Aid solution. They help to hide more serious problems by improving the look of school. According to studies of students and teachers, those who think their dress is good are smart and their behavior is getting better. Politicians prefer school uniforms; many of them support the cause until the school requests more money. Uniforms are usually introduced in schools with low test results in overcrowded conditions.
There is no magical solution to this systematic problem, but we think that there is a way to reduce the pressure and conflict of the staff shortage. Last October, I started testing the Instawork Gigs. This is how companies reserve hotel staff on demand. We learned a lot in the process, and here are some remarkable discoveries. I cried out terribly last minute. Until gigs, many restaurants and catering companies had difficulty in shifting and events if they could not find a staff to cover it. If this meant that operations and customer service will be done more smoothly, the advanced cost of the Gig staff is worth additional money to bring a positive positive experience to the customers of these companies.
Bullying is a problem common to school-aged children. If there is a magic wand, a versatile solution to this problem will be proposed and implemented long ago. You will not think about it, and I will not write it. In order to end bullying, it is important that young people (and in adult life! As we all know, human beings) to fully utilize school culture's full change and social power equitably and equitably It is neither easy nor quick to change the dynamics of it.
ML is not a wand of your work. The first challenge at ML is to grasp the business impact of technologies designed to be promoted. ML is the solution - you first need to define the problem: What business results do you want to achieve through ML? What benefits does ML bring to your customers? ML is a hammer - but if you do not have a nail, the hammer is not particularly useful. To further extend the cliche, ML is a huge variety of hammers, and the nail you have will determine the hammer you will choose and how to use it. The exact problem you are trying to solve determines everything. How to use results, prediction method of model, adjustment method, data to collect and process, algorithm to test, many other problems