Towards AI

JULY 24, 2024

Well, get ready because we’re about to embark on another exciting exploration of explainable AI, this time focusing on Generative AI. Before we dive into the world of explainability in GenAI, it’s worth noting that the tone of this article, like its predecessor, is intentionally casual and approachable.

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Viso.ai

FEBRUARY 12, 2024

True to its name, Explainable AI refers to the tools and methods that explain AI systems and how they arrive at a certain output. Artificial Intelligence (AI) models assist across various domains, from regression-based forecasting models to complex object detection algorithms in deep learning.

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Towards AI

JULY 24, 2024

Well, get ready because we’re about to embark on another exciting exploration of explainable AI, this time focusing on Generative AI. Before we dive into the world of explainability in GenAI, it’s worth noting that the tone of this article, like its predecessor, is intentionally casual and approachable.

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IBM Journey to AI blog

JULY 6, 2023

Python is the most common programming language used in machine learning. Machine learning and deep learning are both subsets of AI. Deep learning algorithms are neural networks modeled after the human brain. It’s unnecessary to know SQL, as programs are written in R, Java, SAS and other programming languages.

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Pickl AI

JANUARY 13, 2025

We aim to guide readers in choosing the best resources to kickstart their AI learning journey effectively. From neural networks to real-world AI applications, explore a range of subjects. Using simple language, it explains how to perform data analysis and pattern recognition with Python and R.

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Pickl AI

AUGUST 1, 2024

Summary : Deep Learning engineers specialise in designing, developing, and implementing neural networks to solve complex problems. They work on complex problems that require advanced neural networks to analyse vast amounts of data. Hyperparameter Tuning: Adjusting model parameters to improve performance and accuracy.

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Dlabs.ai

MAY 22, 2022

Here, we’ll focus more on his AI courses, particularly the one on ML (one of the most popular and highly-rated Machine Learning online courses around). Once complete, you’ll know all about machine learning, statistics, neural networks, and data mining.

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Pickl AI

NOVEMBER 5, 2024

Lack of Transparency Many AI systems operate as “black boxes,” making it difficult for users to understand how decisions are made. Explainable AI (XAI) is crucial for building trust in automated systems. Explainable AI (XAI) There is a growing demand for transparency in AI decision-making processes.

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The MLOps Blog

JUNE 27, 2023

For example, if your team is proficient in Python and R, you may want an MLOps tool that supports open data formats like Parquet, JSON, CSV, etc., Some popular hyperparameter optimization MLOps tools in 2023 Optuna Optuna is an open-source hyperparameter optimization framework in Python. and Pandas or Apache Spark DataFrames.

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Bugra Akyildiz

MAY 25, 2024

Data Tasks ChatGPT can handle a wide range of data-related tasks by writing and executing Python code behind the scenes, without users needing coding expertise. ChatGPT would understand the intent behind the query and translate it into the appropriate SQL or Python code to execute against databases or data warehouses.

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Heartbeat

SEPTEMBER 13, 2023

Distinction Between Interpretability and Explainability Interpretability and explainability are interchangeable concepts in machine learning and artificial intelligence because they share a similar goal of explaining AI predictions. Captum allows users to explain both deep learning and traditional machine learning models.

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Pickl AI

JANUARY 29, 2024

AI comprises Natural Language Processing, computer vision, and robotics. ML focuses on algorithms like decision trees, neural networks, and support vector machines for pattern recognition. Skills Proficiency in programming languages (Python, R), statistical analysis, and domain expertise are crucial.

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Pickl AI

NOVEMBER 18, 2024

Neural networks are powerful for complex tasks, such as image recognition or NLP, but may require more computational resources. Neural networks , while flexible and capable of handling large-scale data, require a lot of data and computing power. Different algorithms are suited to different tasks.

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Mlearning.ai

FEBRUARY 2, 2023

In this article, I show how a Convolutional Neural Network can be used to predict a person's age based on the person's ECG Attia et al 2019 [1], showed that a person's age could be predicted from an ECG using convolutional neural networks (CNN). Ismail Fawaz et al., Data Min Knowl Disc 34 , 1936–1962 (2020).

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Pickl AI

APRIL 2, 2024

Deep Learning: Neural networks with multiple layers used for complex pattern recognition tasks. Tools and Technologies Python/R: Popular programming languages for data analysis and machine learning. Explainable AI (XAI): As AI models become more complex, there’s a growing need for interpretability.

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