Thank You AI

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  • jupyter notebook or Google Colab for machine learning

    This question comes to every machine learning beginner. What should I use? The jupyter notebook or Google Colab for machine learning? We don’t want to be opinionated in this regard. Quite certainly we should not force you to accept one and discard the other. Instead what we are going to place are advantages and disadvantages.…

  • Machine Learning on the Iris dataset

    Machine Learning on the Iris dataset is quite easier than other datasets that are available on the Internet. Let’s learn with examples. We use the Iris dataset as a supervised learning problem.  Because in this case, the prediction of the species of an iris using the measurements is easy. We have seen a few examples…

  • Machine Learning terminologies

    What are the most common machine learning terminologies? Well, if you have read previous sections, you know them already. But we are not going to talk about the terms like supervised learning, unsupervised learning, clustering, regression etc. Google’s Machine Learning Glossary is another good place to start with if you are keen to learn every…

  • Linear regression and Machine Learning relationship

    Certainly there is a linear regression and machine learning relationship that we will discuss in this section. We’ll take help from Iris Data. In the previous section we have seen that linear regression is an algorithm based on supervised learning.  The regression task that it performs is nothing but modeling a target prediction based on…

  • Linear Regression in Machine Learning

    Linear Regression in machine learning is one of the algorithms that help us to establish a relationship between two variables. We have seen before that it belongs to the supervised learning types. Moreover, it helps us to predict the best outcome based on the datasets that we provide to the machine. Now in this first…

  • Regression models in Machine Learning

    Regression models in machine learning can help us determine the relationship between variables. In this section we will understand this topic. Certainly there are different types of regression models in machine learning, but here we will concentrate on linear regression.  As we just said, we try to find the relationship between two variables.  In our…

  • Data Model and Learning in Machine Learning

    In this section we will discuss three key concepts in machine learning – data model and learning. How they are related and their functions. In previous sections we have discussed a few other key concepts, such as Python and scikit-learn, the role of python libraries in machine learning and many more. However, we have not…

  • Python and scikit-learn for Machine Learning

    Why do we need Python and scikit-learn for machine learning? Well, in this short introduction we will try to find out the real reason. Firstly, let’s try to learn why we need Python.  The real reason behind using Python for machine learning is that Python has a ton of libraries designated for machine learning. Secondly,…

  • Machine Learning Python Library

    Which Python library is used for machine learning? Which Python library is used for AI? The answer will point to NumPy and many others. Here very briefly we will take a look at a few libraries that we use quite often in machine learning.  How can we use pandas and matplotlib packages in python and…

  • Is Matplotlib library used for Machine Learning?

    The answer is yes. We use the Matplotlib library or package for machine learning. Why? We will discuss it in this section. And at the same time, we will also discuss why we need a library like Matplotlib in machine learning.  The first and foremost reason is with the help of Matplotlib, we create static,…

  • Python libraries for Machine Learning

    There are a lot of python libraries for machine learning. In this section we will take a look at three major libraries which we need the most. Firstly we will discuss NumPy. It is one of the fundamental libraries that we need for machine learning as well as data science.  What can we do with…

  • How Machine Learning is related to AI?

    We have discussed various types of machine learning methods. However, we need to know How Machine Learning is related to AI? Certainly a section considers machine learning as a subfield of artificial intelligence.  But it could be misleading.  Why? We use the knowledge of machine learning in the study of AI. There is no doubt…

  • Reinforcement Learning in Machine Learning

    What is reinforcement learning in machine learning? We have discussed supervised and unsupervised learning before. However, one of the main types of machine learning is reinforcement learning. In short, it is in between these two types of machine learning processes. As a result, reinforcement learning fills the gap between supervised and unsupervised learning.  Basically in…

  • Machine Learning steps

    What are the basic machine learning steps? If you search in Google, you may find different answers. It might overwhelm a beginner. Firstly, when we utter the word ‘beginner’ we don’t assume that you know nothing about programming and mathematics. Why do we say that? Certainly we will discuss in the coming section. Secondly, it…

  • Unsupervised Learning example

    In the last section we have got an idea about unsupervised learning. To make the concept clear, let’s see a unsupervised learning example. Unsupervised learning helps us to figure out why the dataset is special. Suppose we have different types of cats and different types of dogs.  Therefore, there are many data points that are…

  • Unsupervised Learning in Machine Learning

    We have discussed supervised learning in machine learning in the previous section. Is unsupervised learning just the opposite? Well kind of that. And the story starts from here. Because in supervised learning algorithms we need a teacher who will supervise the learning. Right?  When the learning is unsupervised, we cannot expect a teacher who will…

  • Supervised Learning in Machine Learning

    Supervised learning in machine learning refers to a category of machine learning. In the previous section we have discussed many categories. We have seen one key feature of machine learning is to train a machine based on a training dataset. Right?  However, for doing that we need an algorithm, of course. As a result the…

  • Classification of machine learning

    What do we mean by the classification of machine learning? Firstly, classification is a kind of algorithm that we need to train a machine. Secondly, it is a concept that has an association with supervised learning.  Finally, classification of machine learning basically categorizes a set of training data into classes.  In the previous article we…

  • Training set in machine learning

    In our previous section we have seen how a machine can learn from users. We call these examples training set in machine learning. We indicate each training example as a training instance.  As we have seen earlier, as users mark emails as spams, and move them to spam folders, the system uses them as examples.…

  • Machine learning with examples

    Let’s try to understand machine learning with examples. However, we have already learned that for machine learning what we should do. Right? In our previous section we discussed how through machine learning we train machines to perform various actions. Then how do we define machine learning?  That’s the question a beginner will always ask. In…

  • Train machines through machine learning

    Through machine learning we train machines to perform various actions. A simple example of this action is spam filtering in email. But as long as we talk about these actions that machine learning performs, the sky’s the limit. Let’s take a look at other various tasks or actions. These actions might include predictions, recommendations, estimations,…

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