Data Science Dojo

JUNE 1, 2023

Machine learning courses Top free machine learning courses Here are 9 free machine learning courses from top universities that you can take online to upgrade your skills: 1. The course covers topics such as linear regression, logistic regression, and decision trees.

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Machine Learning Machine Learning Natural Language Processing Deep Learning 195

Dataconomy

OCTOBER 5, 2023

If you are interested in technology at all, it is hard not to be fascinated by AI technologies. Whether it’s pushing the limits of creativity with its generative abilities or knowing our needs better than us with its advanced analysis capabilities, many sectors have already taken a slice of the huge AI pie.

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AI AI Artificial Intelligence Artificial Intelligence 136

IBM Journey to AI blog

DECEMBER 20, 2023

That’s why diversifying enterprise AI and ML usage can prove invaluable to maintaining a competitive edge. 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.

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

Dataconomy

APRIL 4, 2023

LaMDA, GPT, and more… Nowadays, everyone talking about AI models and what they are capable of. The use of AI models is expanding rapidly across all industries. AI’s capacity to find solutions to difficult issues with minimal human input is a major selling point for the technology. What is an AI model?

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K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

LaMDA, GPT, and more… Nowadays, everyone talking about AI models and what they are capable of. The use of AI models is expanding rapidly across all industries. AI’s capacity to find solutions to difficult issues with minimal human input is a major selling point for the technology. What is an AI model?

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Towards AI

APRIL 7, 2024

Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. You just want to create and analyze simple maps not to learn algebra all over again. This function can be improved by AI and ML, which allow GIS to produce insights, automate procedures, and learn from data. Types of Machine Learning for GIS 1.

Machine Learning 105

Machine Learning Machine Learning K-nearest Neighbors Supervised Learning 105

Dataconomy

AUGUST 31, 2023

Machine learning models have already started to take up a lot of space in our lives, even if we are not consciously aware of it. Embracing AI systems and technology day by day, humanity is experiencing perhaps the fastest development in recent years. You want an example: ChatGPT, Alexa, autonomous vehicles and many more on the way.

Machine Learning 136

Machine Learning Machine Learning Supervised Learning Algorithm 136

Dataconomy

MAY 25, 2023

By harnessing the power of AI in IoT, we can create intelligent ecosystems where devices seamlessly communicate, collaborate, and make intelligent choices to improve our lives. Let’s explore the fascinating intersection of these two technologies and understand how AI enhances the functionalities of IoT.

Internet of Things 160

Internet of Things Artificial Intelligence Artificial Intelligence AI 160

Towards AI

MAY 1, 2024

Last Updated on May 1, 2024 by Editorial Team Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. Created by the author with DALL E-3 R has become very ideal for GIS, especially for GIS machine learning as it has topnotch libraries that can perform geospatial computation. Types of machine learning with R.

Machine Learning 98

Machine Learning Machine Learning K-nearest Neighbors Decision Trees 98

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.

Machine Learning 82

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82

Towards AI

FEBRUARY 20, 2024

Last Updated on February 20, 2024 by Editorial Team Author(s): Vaishnavi Seetharama Originally published on Towards AI. Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction Everyone is using mobile or web applications which are based on one or other machine learning algorithms.

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Machine Learning Machine Learning ML ML 109

Pickl AI

SEPTEMBER 16, 2024

Summary: This blog highlights ten crucial Machine Learning algorithms to know in 2024, including linear regression, decision trees, and reinforcement learning. Introduction Machine Learning (ML) has rapidly evolved over the past few years, becoming an integral part of various industries, from healthcare to finance.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Towards AI

APRIL 4, 2024

Last Updated on April 4, 2024 by Editorial Team Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. Created by the author with DALL E-3 Machine learning algorithms are the “cool kids” of the tech industry; everyone is talking about them as if they were the newest, greatest meme.

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K-nearest Neighbors Machine Learning Machine Learning Decision Trees 81

AWS Machine Learning Blog

SEPTEMBER 10, 2024

The remaining features are horizontally appended to the pathology features, and a gradient boosted decision tree classifier (LightGBM) is applied to achieve predictive analysis. To further improve performance, a self-supervised learning-based approach, namely Hierarchical Image Pyramid Transformer (HIPT) ( Chen et al.,

Supervised Learning 91

Supervised Learning Machine Learning Machine Learning AWS 91

Pickl AI

JANUARY 2, 2025

Summary: Entropy in Machine Learning quantifies uncertainty, driving better decision-making in algorithms. It optimises decision trees, probabilistic models, clustering, and reinforcement learning. For example, in decision tree algorithms, entropy helps identify the most effective splits in data.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Clustering 52

Towards AI

JULY 3, 2024

Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. Created by the author with DALL E-3 When deciding who is best at a certain field, the debate can sometimes get messy with no conclusive answer. –Targets: Well-known for strong reliability and accuracy, particularly when working with sizable datasets.

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K-nearest Neighbors Machine Learning Machine Learning Algorithm 105

Mlearning.ai

FEBRUARY 17, 2023

Basically, Machine learning is a part of the Artificial intelligence field, which is mainly defined as a technic that gives the possibility to predict the future based on a massive amount of past known or unknown data. ML algorithms can be broadly divided into supervised learning , unsupervised learning , and reinforcement learning.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Clustering 52

Pickl AI

AUGUST 6, 2023

Machine Learning has become a fundamental part of people’s lives and it typically holds two segments. It includes supervised and unsupervised learning. Supervised Learning deals with labels data and unsupervised learning deals with unlabelled data. You can join Pickl.AI

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Machine Learning Machine Learning Decision Trees Supervised Learning 52

Pickl AI

AUGUST 1, 2023

Types of Machine Learning Model: Machine Learning models can be broadly categorized as: 1. Supervised Learning Models Supervised learning involves training a model on labelled data, where the input features and corresponding target outputs are provided. regression, classification, clustering).

Machine Learning 52

Machine Learning Machine Learning Support Vector Machines Decision Trees 52

Pickl AI

JULY 12, 2024

Introduction Artificial Intelligence (AI) transforms industries by enabling machines to mimic human intelligence. Python’s simplicity, versatility, and extensive library support make it the go-to language for AI development. Python is renowned for its simplicity and versatility, making it an ideal choice for AI applications.

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Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

AUGUST 28, 2024

In this blog, we will delve into the world of classification algorithms, exploring their basics, key algorithms, how they work, advanced topics, practical implementation, and the future of classification in Machine Learning. Examples include Logistic Regression, Support Vector Machines (SVM), Decision Trees, and Artificial Neural Networks.

Machine Learning 52

Machine Learning Machine Learning Algorithm K-nearest Neighbors 52

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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Machine Learning Machine Learning Decision Trees Algorithm 52

Pickl AI

DECEMBER 9, 2024

For example, a model may assume that similar inputs produce similar outputs in supervised learning. In contrast, decision trees assume data can be split into homogeneous groups through feature thresholds. Algorithmic Bias Algorithmic bias arises from the design of the learning algorithm itself.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Natural Language Processing 52

Pickl AI

MARCH 6, 2024

These interview questions for Machine Learning delve into foundational concepts like supervised and unsupervised learning, model evaluation techniques, and algorithm optimization. Employers seek candidates who can demonstrate their understanding of key machine learning algorithms.

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Machine Learning Machine Learning Supervised Learning Algorithm 52

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.

Data Analyst 52

Data Analyst Data Science 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

JULY 31, 2023

Understanding Eager Learning Eager Learning, also known as “Eager Supervised Learning,” is a widely used approach in Machine Learning. Random Forest : Random Forest is an ensemble learning method that combines multiple Decision Trees to improve prediction accuracy and reduce overfitting.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

Dataconomy

MARCH 13, 2023

The creation of artificial intelligence (AI) has long been a dream of scientists, engineers, and innovators. With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. How to create an artificial intelligence?

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Artificial Intelligence Artificial Intelligence Natural Language Processing Algorithm 98

AWS Machine Learning Blog

OCTOBER 30, 2024

Solution overview In this post, we demonstrate how to fine-tune a sentence transformer with Amazon product data and how to use the resulting sentence transformer to improve classification accuracy of product categories using an XGBoost decision tree. Kara is passionate about innovation and continuous learning.

Machine Learning 106

Machine Learning Machine Learning AWS Data Scientist 106

Pickl AI

FEBRUARY 7, 2025

Summary: Machine Learning and Deep Learning are AI subsets with distinct applications. Understanding their differences helps choose the right approach for AI-driven innovations across various industries. What is Machine Learning? The model learns from the input-output pairs and predicts outcomes for new data.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Pickl AI

OCTOBER 24, 2024

Summary: This article compares Artificial Intelligence (AI) vs Machine Learning (ML), clarifying their definitions, applications, and key differences. While AI aims to replicate human intelligence across various domains, ML focuses on learning from data to improve performance. What is Artificial Intelligence?

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Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 52

Mlearning.ai

OCTOBER 2, 2023

The two main categories of feature selection are supervised and unsupervised machine learning techniques. Image by author Let’s kick off with supervised learning. On the other hand, unsupervised machine learning deals with unlabeled data and aims to discover hidden patterns within that data. Here’s the overview.

Machine Learning 98

Machine Learning Machine Learning Supervised Learning Algorithm 98

Mlearning.ai

NOVEMBER 29, 2023

The downside of overly time-consuming supervised learning, however, remains. Classic Methods of Time Series Forecasting Multi-Layer Perceptron (MLP) Univariate models can be used to model univariate time series prediction machine learning problems. In its core, lie gradient-boosted decision trees.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

AWS Machine Learning Blog

FEBRUARY 28, 2023

Businesses looking for a fully-managed AWS AI service for fraud detection can also use Amazon Fraud Detector , which you can use to identify suspicious online payments, detect new account fraud, prevent trial and loyalty program abuse, or improve account takeover detection. In his free time, he enjoys reading history and science fiction.

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AWS Machine Learning Machine Learning Algorithm 101

Pickl AI

FEBRUARY 12, 2024

Machine Learning Algorithms Candidates should demonstrate proficiency in a variety of Machine Learning algorithms, including linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks. Differentiate between supervised and unsupervised learning algorithms.

Data Science 52

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phData

AUGUST 24, 2023

With a modeled estimation of the applicant’s credit risk, lenders can make more informed decisions and reduce the occurrence of bad loans, thereby protecting their bottom line. 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.

ML 52

ML ML Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 28, 2024

These techniques span different types of learning and provide powerful tools to solve complex real-world problems. Supervised Learning Supervised learning is one of the most common types of Machine Learning, where the algorithm is trained using labelled data.

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Machine Learning Machine Learning ML ML 52