Mlearning.ai

MARCH 13, 2023

Photo by Andy Kelly on Unsplash Choosing a machine learning (ML) or deep learning (DL) algorithm for application is one of the major issues for artificial intelligence (AI) engineers and also data scientists. Explore algorithms: Research and explore different algorithms that are desired for your problem.

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Pickl AI

JULY 7, 2023

Are you ready to take your machine learning algorithms to the next level? Say hello to Gradient Boosting Algorithm! Gradient boosting is not just your regular algorithm; it’s a functional gradient algorithm that works wonders in the world of machine learning. What is Gradient Boosting?

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Google Research AI blog

FEBRUARY 7, 2023

The explosion in deep learning a decade ago was catapulted in part by the convergence of new algorithms and architectures, a marked increase in data, and access to greater compute. Below, we highlight a panoply of works that demonstrate Google Research’s efforts in developing new algorithms to address the above challenges.

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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. These nuanced algorithms can lead to more accurate and reliable credit scores and decisions. loan default or not).

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IBM Journey to AI blog

FEBRUARY 23, 2024

Conversational artificial intelligence (AI) leads the charge in breaking down barriers between businesses and their audiences. This class of AI-based tools, including chatbots and virtual assistants, enables seamless, human-like and personalized exchanges.

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Mlearning.ai

APRIL 10, 2023

So without any further due, let’s do it… Read the full article here —  [link] Lazypredict LazyPredict is a Python package that helps data scientists quickly build supervised machine-learning models without having to spend time on the tedious and time-consuming task of exploring various algorithms and optimizing hyperparameters.

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Towards AI

APRIL 7, 2024

Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. Created by the author with DALL E-3 Statistics, regression model, algorithm validation, Random Forest, K Nearest Neighbors and Naïve Bayes— what in God’s name do all these complicated concepts have to do with you as a simple GIS analyst?

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Dataconomy

MAY 25, 2023

By leveraging advanced algorithms and machine learning techniques, IoT devices can analyze and interpret data in real-time, enabling them to make informed decisions and take autonomous actions. Let’s explore the fascinating intersection of these two technologies and understand how AI enhances the functionalities of IoT.

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Mlearning.ai

FEBRUARY 17, 2023

ML algorithms can be broadly divided into supervised learning , unsupervised learning , and reinforcement learning. Strictly, everything that I said earlier is based on Machine learning algorithms and, of course, strong math and theory of algorithms behind them. In this article, I will cover all of them.

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Dataconomy

AUGUST 9, 2023

This is where the power of machine learning (ML) comes into play. Machine learning algorithms, with their ability to recognize patterns, anomalies, and trends within vast datasets, are revolutionizing network traffic analysis by providing more accurate insights, faster response times, and enhanced security measures.

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Towards AI

SEPTEMBER 10, 2023

Last Updated on September 11, 2023 by Editorial Team Author(s): Mariya Mansurova Originally published on Towards AI. I’ve passed many ML courses before, so that I can compare. The course covers the basics of Deep Learning and Neural Networks and also explains Decision Tree algorithms.

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Pickl AI

JULY 14, 2023

Even in the time of pandemic, AI has enabled in providing technical solutions to the people in terms of information inflow. Therefore, AI has been evolving since years now and is currently at its peak of development. AI has been disrupting every industry in the world today and will supposedly make larger swings in the next 5 years.

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Data Science Dojo

JUNE 1, 2023

Machine Learning with TensorFlow by Google AI This is a beginner-level course that teaches you the basics of machine learning using TensorFlow , a popular machine-learning library. The course covers topics such as linear regression, logistic regression, and decision trees.

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Pickl AI

APRIL 5, 2023

ML forms the underlying platform for several new developments. Hence, it has also triggered the demand for ML experts. However, if you are new to the tech domain and want to learn Machine Learning for free, then in this blog, we will take you through the 3 best options to start your ML learning journey. Lakhs to ₹ 28.4

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Pickl AI

AUGUST 6, 2023

What is Regression in ML? Regression Machine Learning algorithms is a statistical method that you can use to model the relationship between dependent variables and one or more independent variables. Effectively, regression algorithms helps in determining the best-fit line.

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Mlearning.ai

JULY 24, 2023

This article will cover the basics of Decision Trees and XGBoost, and demonstrate how to implement the latter for classifying celestial objects in the night sky as either a Galaxy, Star, or Quasar. Photo by Nathan Anderson on Unsplash Brief Intro to ML Algorithms A decision tree is a widely used algorithm in machine learning.

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Ocean Protocol

MAY 2, 2024

Participants demonstrated outstanding ability in utilizing ML and AI to examine and predict startup success within the venture capital landscape and refine investment strategies. Prevalence of AI and Tech Startups in Investment Portfolios Over the last decade, investments in AI and technology-focused startups have increased by 35%.

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Pickl AI

APRIL 3, 2023

Apparently, ML algorithms ensure to train of the data enabling the new data input to make compelling predictions and deliver accurate results. Supervised Learning is the type of Machine Learning where the training of an algorithm takes place using labelled data. What is Supervised Learning? What is Unsupervised Learning?

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Defined.ai blog

AUGUST 10, 2023

Welcome to the world of financial data, where every digit has a story to tell, and Artificial Intelligence (AI) assumes the role of a compelling storyteller. With more companies shifting towards data-driven decision-making, understanding financial data and leveraging AI’s power has never been more crucial.

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The MLOps Blog

DECEMBER 19, 2022

As Data Scientists, we all have worked on an ML classification model. In this article, we will talk about feasible techniques to deal with such a large-scale ML Classification model. In this article, you will learn: 1 What are some examples of large-scale ML classification models? Let’s take a look at some of them.

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Heartbeat

SEPTEMBER 13, 2023

Source: ResearchGate Explainability refers to the ability to understand and evaluate the decisions and reasoning underlying the predictions from AI models (Castillo, 2021). Explainability techniques aim to reveal the inner workings of AI systems by offering insights into their predictions.

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Mlearning.ai

DECEMBER 31, 2023

Principles of Explainable AI( Source ) Imagine a world where artificial intelligence (AI) not only makes decisions but also explains them as clearly as a human expert. This isn’t a scene from a sci-fi movie; it’s the emerging reality of Explainable AI (XAI). What is Explainable AI?

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Pickl AI

MAY 17, 2023

However, while working on a Machine Learning algorithm , one may come across the problem of underfitting or overfitting. Training data plays an important role in deciding the effectiveness of an ML model. Most of the time, to avoid the underfitting issue, the ML expert ends up adding too many features to it, leading to overfitting.

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Towards AI

APRIL 11, 2023

Last Updated on April 12, 2023 by Editorial Team Author(s): Surya Maddula Originally published on Towards AI. Classification In Classification, we use an ML Algorithm to classify the digit based on its features. Support Vector Machines (SVMs) are another ML models that can be used for HDR. Implementation of […]

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ODSC - Open Data Science

AUGUST 15, 2023

Advancements in data science and AI are coming at a lightning-fast pace. Troubleshooting Search and Retrieval with LLMs Xander Song | Machine Learning Engineer and Developer Advocate | Arize AI Some of the major challenges in deploying LLM applications are the accuracy of results and hallucinations. Check out a few of them below.

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How to Learn Machine Learning

DECEMBER 4, 2022

In recent years, artificial intelligence (AI) has made significant advances in its ability to complete various tasks that were once thought to be exclusive to humans. AI is not yet able to write complex codes as well as a human programmer, but it is becoming increasingly capable of completing this task.

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ODSC - Open Data Science

SEPTEMBER 18, 2023

Especially now with the growth of generative AI and prompt engineering  — both skills that use NLP — now’s a good time to get into the field while it’s hot with this introduction to NLP course. This 7-part course will give you everything you need to get started learning NLP, including ML for NLP, tokenization, and more.

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Flipboard

NOVEMBER 21, 2023

Because we have a model of the system and faults are rare in operation, we can take advantage of simulated data to train our algorithm. First, we extract features from a subset of the full dataset using the Diagnostic Feature Designer app, and then run the model training locally with a MATLAB decision tree model.

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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. The quality and quantity of data are crucial for the success of an AI system.

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IBM Journey to AI blog

JULY 6, 2023

Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on learning from what the data science comes up with. Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention.

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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. Two of the most well-known subfields of AI are machine learning and deep learning. In both cases, algorithms are trained to generate predictions or judgments based on data inputs. What is Machine Learning?

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AWS Machine Learning Blog

JUNE 22, 2023

Light & Wonder teamed up with the Amazon ML Solutions Lab to use events data streamed from LnW Connect to enable machine learning (ML)-powered predictive maintenance for slot machines. Predictive maintenance is a common ML use case for businesses with physical equipment or machinery assets.

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AWS Machine Learning Blog

MAY 8, 2024

They focused on improving customer service using data with artificial intelligence (AI) and ML and saw positive results, with their Group AI Maturity increasing from 50% to 80%, according to the TM Forum’s AI Maturity Index. Concurrently, the ensemble model strategically combines the strengths of various algorithms.

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Pickl AI

JANUARY 3, 2024

Feature engineering in machine learning is a pivotal process that transforms raw data into a format comprehensible to algorithms. The growing application of Machine Learning also draws interest towards its subsets that add power to ML models. Hence, it is important to discuss the impact of feature engineering in Machine Learning.

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Ocean Protocol

MARCH 11, 2024

METAR, Miami International Airport (KMIA) on March 9, 2024, at 15:00 UTC In the recently concluded data challenge hosted on Desights.ai , participants used exploratory data analysis (EDA) and advanced artificial intelligence (AI) techniques to enhance aviation weather forecasting accuracy. Unlike other platforms, data scientists keep the IP.

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Pickl AI

SEPTEMBER 3, 2023

In 2023, the expected reach of the AI market is supposed to reach the $500 billion mark and in 2030 it is supposed to reach $1,597.1 49% of companies in the world that use Machine Learning and AI in their marketing and sales processes apply it to identify the prospects of sales.

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Pickl AI

NOVEMBER 8, 2023

Decision Tree) Making Predictions Evaluating Model Accuracy (Classification) Feature Scaling (Standardization) Getting Started Before diving into the intricacies of Scikit-Learn, let’s start with the basics. Model Selection Picking the Right Algorithm Scikit-Learn boasts a variety of Machine Learning algorithms.

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