How to Learn Python from Scratch

If you want to learn programming today, the easiest and most popular language is Python . It is not only easy to learn but you can do many things through it – like web development, data science, artificial intelligence, automation, machine learning, scripting, and much more. In this blog, we will see step-by-step how to learn Python from zero , what resources to use, what projects to work on and how to go from a beginner to an expert. Why learn Python? There are many benefits of learning Python: This is a simple and readable language, which even a beginner can understand easily. Python is open-source i.e. it is available for free. It has many libraries and frameworks like Django, Flask, Pandas, NumPy, TensorFlow etc. The demand for Python is increasing very rapidly in the job sector. Step 1: Start with the Basics If you are a complete beginner, first install Python on your computer. You can download it from the official website – python.org. After installing, you ...
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What's the Difference Between AI and Machine Learning?

Creating intelligent agents—systems that can perceive their surroundings, learn from past experiences, and make decisions to accomplish certain objectives—is the focus of the large subject of computer science known as artificial intelligence (AI). By essentially imitating human intellect, artificial intelligence (AI) enables robots to carry out activities that otherwise require human reasoning.

Difference Between AI and Machine Learning

In contrast, machine learning (ML) is a branch of artificial intelligence that focuses on techniques that let computers learn from data without the need for explicit programming. Machine learning algorithms find patterns in data and use those patterns to anticipate or decide.

Use this analogy to demonstrate the distinction:
  • The driver's license is AI: It's the general idea that a computer can carry out tasks in an intelligent manner.
  • The driving skill is machine learning, which is a particular method that allows a computer to pick up driving skills via practice and observation.





Important Distinctions:
  • Scope: Artificial Intelligence (AI) is a vast field that includes a variety of methods, such as neural networks, rule-based systems, and expert systems. ML, on the other hand, mostly uses algorithms and statistical methods.
  • AI's objective is to develop intelligent agents that are capable of simulating human intellect. The goal of machine learning is to create algorithms that let computers learn from data.
  • Methods: AI may employ a number of methods, including as neural networks, rule-based systems, and expert systems. To find patterns in data, machine learning mostly use statistical methods and algorithms.




  • Applications: AI is used in many different fields, such as robotics, computer vision, and natural language processing. Predictive analytics, speech recognition, and picture recognition are the main applications of machine learning.
Machine learning is a potent tool in the AI toolbox, even if AI covers a wider variety of methods and applications. We can better appreciate their potential to transform a variety of businesses and enhance our lives if we know the difference between the two. 

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