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Showing posts with the label Learning

Don't get bogged down in machine learning and natural language processing, that's the difference

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 Don't get bogged down in machine learning and natural language processing, that's the difference Machine Learning (ML) is a phrase that is being heard frequently in recent times due to AI tools. Because using machine learning models, AI writes like a human. With the rise of AI, Natural Language Processing (NLP) is another buzzword. However, it is common to say that machine learning and natural language processing are synonymous. But although they are related to each other, there are definitely differences. Today in this article we will discuss those differences and how they work together in an AI tool: What is machine learning? One area of AI is machine learning. It is especially used in developing algorithms and mathematical models. Such models can develop themselves by analyzing data. Without the developer's instructions, those models can use data streams (transferring data at high speed) to learn patterns, make inferences, or make decisions. Similarly, they enable machi

Deep Learning with Python

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Deep Learning with Python Deep learning is a type of machine learning that uses algorithms called neural networks to make predictions or take actions based on data. It is a subset of artificial intelligence (AI) and is particularly well-suited to tasks that require the ability to learn and adapt over time, such as image and speech recognition.

Reinforcement learning

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Reinforcement learning Reinforcement learning is a type of machine learning that focuses on training algorithms to make decisions in a dynamic environment. Unlike supervised learning, in which the algorithm is given the correct output for each example in the training data, reinforcement learning algorithms must learn through trial and error, receiving feedback in the form of rewards or punishments for their actions.

Deep learning

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Deep learning Deep learning is a type of machine learning that involves the use of algorithms called artificial neural networks to learn from data. Unlike traditional machine learning algorithms, which are designed to learn from a limited set of features, deep learning algorithms can learn from a vast amount of data and discover hidden patterns and relationships in the data.

Machine learning

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Machine learning Machine learning is a type of artificial intelligence that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. This is achieved through the use of algorithms that iteratively learn from data, allowing the software to improve its performance on a specific task over time.

TensorFlow Privacy : Learning with Differential Privacy for Training Data

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Introducing TensorFlow Privacy: Learning with different privacy for training data Today, we are excited to announce TensorFlow Privacy (GitHub), an open-source library that makes it easier for developers to not only train machine-learning models with privacy but also to advance the state of the art with machine learning. Strict privacy guarantee. Modern machine learning is increasingly used to create amazing new technologies and user experiences, many of which involve training machines to learn responsibility from sensitive data, such as personal photos or emails. Ideally, the parameters of trained machine-learning models should encode general patterns rather than facts about specific training examples. To ensure this, and to give strict privacy guarantees if the training data is sensitive, it is possible to use technology based on different privacy principles. In particular, when trained in user data, those technologies offer strict mathematical guarantees that the model wil