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آماده سازی و پردازش دقیق داده ها

داده های تعلیمی(تمرینی) عبارتند از داده های نشانه گذاری شده (برچسب دار) که برای آموزش مدل ها و یا الگوریتم های یادگیری ماشینی به کار می روند؛

For example, if you are trying to build a model for a self-driving car, the training data will include images and videos labeled to identify cars vs street signs vs people. If you are creating a customer service chatbot, the data may be all the different ways to ask “what is my account balance?” both in text and audio, which is then translated to different languages.

Training data is paramount to the success of any AI model or project. Think of it as garbage in, garbage out. If you train a model with poor-quality data, then how can you expect it to perform? You can’t and it won’t.

یادگیری ماشین چیست؟

"Machine learning" is the idea that there are generic algorithms that can tell you something interesting about a set of data without you having to write any custom code specific to the problem. Instead of writing code, you feed data to the generic algorithm and it builds its own logic based on the data.

آماده سازی اطلاعات برای یادگیری ماشین چگونه انجام می شود؟

Data preparation (also referred to as “data preprocessing”) is the process of transforming raw data so that data scientists and analysts can run it through machine learning algorithms to uncover insights or make predictions. Improperly formatted structured data.

Artificial Intelligence Vocabulary

What is train data and test data in machine learning?

The training data is used to make sure the machine recognizes patterns in the data, the cross-validation data is used to ensure better accuracy and efficiency of the algorithm used to train the machine, and the test data is used to see how well the machine can predict new answers based on its training.

Five steps to put
AI into practice

Step 1: “Follow the money” to decide where to test AI pilot use-cases.

Step 2: Understand the status quo, its pain points and your AI ambition level. …

Step 3: Develop AI use cases based on customer needs. …

Step 4: Prioritize use cases based on business value and implementation complexity. …

Step 5: Start today.

How do you prepare data for classification?

You can collect training data by drawing ROIs for each known feature type on a high-resolution orthorectified photograph that is co-registered with the image you will classify. Or you could conduct a field study to collect ground-truth samples, then convert the data into ROIs.

Annotation نشانه گذاری

نشانه گذاری تصاویر با هدف شناساندن و معرفی شی یا موجود داخل تصویر به ماشین انجام می شود

در این روش پس از محاط کردن مستطیل بر خطوط پیرامون شکل، نام شی برچسب گزاری (تگ کردن) می شود