Artificial Intelligence (AI) vs Machine Learning vs Deep Learning vs Data Science

Artificial intelligence is a field where set of techniques are used to make computers as smart as humans. There are certain tasks where human outperform computers such as image recognition, cognitive thinking, creativity, driving cars etc. Machine learning is a sub domain of artificial intelligence where set of statistical and neural network based algorithms are used for training a computer in doing a smart task. Deep learning is all about neural networks. Deep learning is considered to be a sub field of machine learning. Pytorch and Tensorflow are two popular frameworks that can be used in doing deep learning.
Data science on the other hand a field where data is used to generate business insights. It can use machine learning techniques but data science can be done without using machine learning as well. One can use Microsoft excel to draw insights from data. Visualization and BI tools such as tableau and power BI can be used to plot powerful business reports that can give lots of insights about a business.

#machine-learning #artificial-intelligence #data-science #python #developer

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Artificial Intelligence (AI) vs Machine Learning vs Deep Learning vs Data Science
Verner  Hahn

Verner Hahn


AI vs Machine Learning vs Deep Learning | AI vs ML vs DL | Machine Learning Training with Python

This video is about the difference between the three terms Artificial Intelligence, Machine Learning & Deep Learning.
AI vs ML vs DL

Download the Course Curriculum File from here:

#machine-learning #deep-learning #artificial-intelligence #data-science #ai

Sofia  Maggio

Sofia Maggio


Cheat Sheets for Artificial Intelligence, Neural Networks, Machine Learning, Deep Learning

This cheat sheet helps you to choose the proper estimate for the task that is the hardest portion of the work. With modern computer technology, today’s machine learning isn’t like machine learning from the past.

The notion that computer may learn without being trained to do certain tasks came from pattern recognition researchers interested in artificial intelligence sought to explore if computers could learn from the information.

The iterative component of machine education is crucial because they may adjust autonomously when models are exposed to fresh data. From past calculations, they learn to create dependable, repeatable judgments and results. It’s not a new science, but a new one.


The usage of programming and even equipment is automation for computerized commands. AI, again, is the robots’ ability to reproduce human habits and thinking and get more clever all the time. It is important, while a misleadingly sharp computer may learn and modify its job as it receives new information, it cannot completely replace people. Everything is equal, it’s a resource, not a risk.

Python for Data Science

A language of programming is a batch of instructions producing input, which is termed output productivity. Languages of programming are built on algorithms and establish a framework for maximizing access and progress. Essentially, apps, websites, and programs are valued for development. Python is the best language for Data Science and it has several syntactic words and conditions. Specific experiences include being a knowledgeable coder.
  • TensorFlow
  • Scikit-Learn
  • Keras
  • Numpy
  • Data Wrangling
  • Scipy
  • Matplotlib:
  • Data Visualization
  • PySpark
  • Big-O
  • Neural Networks

#artificial-intelligence #machine-learning #deep-learning #big-data #deep learning #machine learning

Dianna  Farrell

Dianna Farrell


Deep Learning vs Machine Learning vs Artificial Intelligence vs Data Science

This “Deep Learning vs Machine Learning vs AI vs Data Science” video talks about the differences and relationship between Artificial Intelligence, Machine Learning, Deep Learning, and Data Science.

Enjoy the video!

#deep-learning #machine-learning #artificial-intelligence #data-science #developer

Michael  Hamill

Michael Hamill


How are deep learning, artificial intelligence and machine learning related

So you find yourself saying “Well, it’s time we step on to digital transformation for our organization. Let’s look at the technologies we can implement.”

When you complete saying that sentence, the first thing that comes to your mind is Artificial Intelligence(AI) systems. You think of intelligence machines that can execute tasks on their human and make insightful decisions — like Sophie or Watson.

“So artificial intelligence(AI) is what we need.”, you say to yourself

Yes and No. Yes, in the sense that AI machines are useful for digital transformation.

No in the sense that you will integrate Artificial Intelligence with the help of algorithms which build the foundation for these systems. So you are not integrating AI but the algorithms that make AI machines work.

Here’s a simple explanation — The process that you want to improve through digital transformation will be optimized through AI machines.

These machines will be developed using a subset of AI — Machine Learning Algorithms. To go further deep — your organization can also implement Deep Learning — a subset of Machine Learning.

#artificial-intelligence #machine-intelligence #deep-learning #machine-learning #machine-learning-ai

Artificial Intelligence vs. Machine Learning vs. Deep Learning

Simple explanations of Artificial Intelligence, Machine Learning, and Deep Learning and how they’re all different

#artificial-intelligence #deep-learning #ai #data-science #machine-learning