Pickl AI

JULY 12, 2024

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. It equips you to build and deploy intelligent systems confidently and efficiently.

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Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Dataconomy

OCTOBER 5, 2023

Artificial intelligence, one of the most talked about topics in today’s technology world, has played a huge role in bringing many things into our lives, especially in the last five years. But does that mean artificial intelligence is perfect? With the model selected, the initialization of parameters takes place.

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IBM Journey to AI blog

DECEMBER 20, 2023

What is machine learning? ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. Here, we’ll discuss the five major types and their applications. the target or outcome variable is known).

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Machine Learning Machine Learning Supervised Learning Clustering 92

Pickl AI

SEPTEMBER 23, 2024

Summary: The blog explores the synergy between Artificial Intelligence (AI) and Data Science, highlighting their complementary roles in Data Analysis and intelligent decision-making. Introduction Artificial Intelligence (AI) and Data Science are revolutionising how we analyse data, make decisions, and solve complex problems.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

IBM Journey to AI blog

DECEMBER 19, 2023

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.

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Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82

Dataconomy

APRIL 4, 2023

Artificial intelligence (AI) is a broad term that encompasses the ability of computers and machines to perform tasks that normally require human intelligence, such as reasoning, learning, decision-making, and problem-solving. An AI model is a crucial part of artificial intelligence.

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Dataconomy

APRIL 4, 2023

Artificial intelligence (AI) is a broad term that encompasses the ability of computers and machines to perform tasks that normally require human intelligence, such as reasoning, learning, decision-making, and problem-solving. An AI model is a crucial part of artificial intelligence.

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K-nearest Neighbors Decision Trees AI AI 91

Becoming Human

MARCH 16, 2023

How AI is applied Artificial Intelligence covers various technologies and approaches that involve using sophisticated computational methods to mimic elements of human intelligence such as visual perception, speech recognition, decision-making, and language understanding. And that’s where AI drug discovery could play a role.

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Mlearning.ai

FEBRUARY 17, 2023

A complete explanation of the most widely practical and efficient field, that nowadays has an impact on every industry Photo by Thomas T on Unsplash Machine learning has become one of the most rapidly evolving and popular fields of technology in recent years. In this article, I will cover all of them. Reward(1) or punishment(0).

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Clustering 52

Pickl AI

SEPTEMBER 10, 2024

Despite its limitations, the Perceptron laid the groundwork for more complex neural networks and Deep Learning advancements. Introduction The Perceptron is one of the foundational concepts in Artificial Intelligence and Machine Learning. Frequently Asked Questions What is a Perceptron?

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Deep Learning Deep Learning Machine Learning Machine Learning 52

Pickl AI

FEBRUARY 7, 2025

Introduction In todays world of AI, both Machine Learning (ML) and Deep Learning (DL) are transforming industries, yet many confuse the two. While both are subsets of Artificial Intelligence, they differ significantly regarding techniques and applications. What is Machine Learning?

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Deep Learning Deep Learning Machine Learning Machine Learning 52

IBM Journey to AI blog

JULY 6, 2023

What is machine learning? Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on learning from what the data science comes up with. Machine learning can then “learn” from the data to create insights that improve performance or inform predictions.

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Machine Learning Machine Learning Data Science Big Data 70

Pickl AI

NOVEMBER 18, 2024

Ethical considerations are crucial in developing fair Machine Learning solutions. Basics of Machine Learning Machine Learning is a subset of Artificial Intelligence (AI) that allows systems to learn from data, improve from experience, and make predictions or decisions without being explicitly programmed.

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Pickl AI

SEPTEMBER 12, 2024

Artificial Intelligence (AI): A branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. Association Rule Learning: A rule-based Machine Learning method to discover interesting relationships between variables in large databases.

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Data Analyst Data Science Machine Learning Machine Learning 52

Heartbeat

OCTOBER 25, 2023

The development of explainable and interpretable machine learning models will enhance the trustworthiness of predictions and enable researchers to gain deeper insights into the underlying biological mechanisms.

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Heartbeat

OCTOBER 11, 2023

A key component of artificial intelligence is training algorithms to make predictions or judgments based on data. 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.

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Deep Learning Deep Learning Machine Learning Machine Learning 52

Pickl AI

AUGUST 9, 2024

Students should learn how to leverage Machine Learning algorithms to extract insights from large datasets. Key topics include: Supervised Learning Understanding algorithms such as linear regression, decision trees, and support vector machines, and their applications in Big Data.

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Big Data Big Data Big Data Analytics Big Data Analytics 52

PyImageSearch

SEPTEMBER 16, 2024

Machine Learning Methods Machine learning methods ( Figure 7 ) can be divided into supervised, unsupervised, and semi-supervised learning techniques. Figure 7: Machine learning methods for identifying outliers or anomalies (source : Turing ). unusual network traffic patterns).

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Clustering Algorithm Machine Learning Machine Learning 57

phData

AUGUST 24, 2023

Now that we have a firm grasp on the underlying business case, we will now define a machine learning pipeline in the context of credit models. Machine learning in credit scoring and decisioning typically involves supervised learning , a type of machine learning where the model learns from labeled data.

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Pickl AI

MAY 31, 2023

Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow. Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Mlearning.ai

JANUARY 31, 2023

left: neutral pose — do nothing | right: fist  — close gripper | Photos from myo-readings-dataset left: extension  — move forward | right: flexion  — move backward | Photos from myo-readings-dataset This project uses the scikit-learn implementation of a Support Vector Machine (SVM) trained for gesture recognition.

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