Remove Decision Trees Remove Deep Learning Remove Natural Language Processing Remove Support Vector Machines
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Machine Learning vs. Deep Learning - A Comparison

Heartbeat

This process is known as machine learning or deep learning. Two of the most well-known subfields of AI are machine learning and deep learning. What is Deep Learning? This is why the technique is known as "deep" learning.

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Generative vs Discriminative AI: Understanding the 5 Key Differences

Data Science Dojo

A visual representation of discriminative AI – Source: Analytics Vidhya Discriminative modeling, often linked with supervised learning, works on categorizing existing data. This breakthrough has profound implications for drug development, as understanding protein structures can aid in designing more effective therapeutics.

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How to build a Machine Learning Model?

Pickl AI

As technology continues to impact how machines operate, Machine Learning has emerged as a powerful tool enabling computers to learn and improve from experience without explicit programming. In this blog, we will delve into the fundamental concepts of data model for Machine Learning, exploring their types.

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Named Entity Recognition With SpaCy

Heartbeat

In the same way, ML algorithms can be trained on large datasets to learn patterns and make predictions based on that data. Named entity recognition (NER) is a subtask of natural language processing (NLP) that involves automatically identifying and classifying named entities mentioned in a text. synonyms).

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Creating an artificial intelligence 101

Dataconomy

With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. However, the process of creating AI can seem daunting to those who are unfamiliar with the technicalities involved.

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Where AI is headed in the next 5 years?

Pickl AI

Machine Learning and Neural Networks (1990s-2000s): Machine Learning (ML) became a focal point, enabling systems to learn from data and improve performance without explicit programming. Techniques such as decision trees, support vector machines, and neural networks gained popularity.

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Data science vs. machine learning: What’s the difference?

IBM Journey to AI blog

Python is the most common programming language used in machine learning. Machine learning and deep learning are both subsets of AI. Deep learning teaches computers to process data the way the human brain does.