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Lobe AI
              Lobe is  a  simple,  no-code tool  created by  Microsoft  in  2015.  It  helps  users  build  and train machine  learning
              models without any coding skills. It’s designed for people who want to create AI models for tasks like image
              classification, but don’t have a background in programming or data science. Lobe automatically trains models
              based on uploaded images and allows users to export trained models for deployment.
              Teachable Machine
              Teachable Machine is a web-based tool developed by
                                                                          Population
              Google in November 2017. It allows anyone to create
              machine  learning  models  easily,  without  needing  any
                                                                                            Sampling
              coding  knowledge.  It  is  especially  designed  to  help     Sample                           Sample
              people train models for tasks such as image recognition,
              sound  classification,  and  pose  detection,  using  their
              own  data.  The  main  idea  behind  Teachable  Machine   Data under investigation
              is  to  make  machine  learning  accessible  to  everyone,   (very large, difficult to use)
              whether you’re a beginner or not.

                       Important Concepts in Statistics


              Before we go for Statistical Analysis, we need to understand few terms of Statistics.
              Population


              The complete collection of raw data available for a test or experiment is referred to as the population. It is not
              always feasible to analyse patterns and trends across the entire population. Instead, you can select a sample—a
              subset of the population selected for analysis. It should be representative of the population to ensure accurate
              conclusions.

              Statistical Sampling

              Statistical sampling is a method used to select a smaller group (sample) from a larger group (population) to
              study. Instead of analysing every individual in a dataset, researchers study the sample and generalize findings to
              the whole population. Sampling will help you:
                 • Save time as you don’t need to study the complete set of data.
                 • It saves money and resources.
                 • A well-chosen sample can give you results that are close to what you’d get if you studied everyone.

              Let’s say you want to know the average age of people who visit a park. You can’t ask everyone who visits the park,
              but you can pick a small group of people at random to ask. If you ask the right group of people, their ages will give
              you a good estimate of the average age of all visitors.

              Descriptive Statistics

              Descriptive  Statistics  summarise  and  describe  a  set  of  data.  Instead  of  examining  every  individual  number,
              descriptive statistics helps us see patterns, trends, and key points about the data, making it easier to understand.
              It helps answer questions like “What is typical?” or “What is the most common?” We measure Descriptive Statistics
              using:
                 • Mean (Average): The mean is the most common way to describe the “central” or “typical” value in a set of data.
                It is also known as the average. To find the mean, you add up all the numbers in your data and then divide by
                how many numbers there are.

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