Analytics Vidhya

MAY 14, 2023

It is crucial for them to learn the correct strategy to identify or develop models for solving equations involving distinct variables. Thus, understanding the disparity between two fundamental algorithms, Regression vs Classification, becomes essential. […] The post Regression vs Classification in Machine Learning Explained!

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Marktechpost

MAY 8, 2024

Over the past decade, advancements in deep learning and artificial intelligence have driven significant strides in self-driving vehicle technology. Deep learning and AI technologies play crucial roles in both modular and End2End systems for autonomous driving. Classical methodologies for these tasks are also explored.

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Marktechpost

NOVEMBER 20, 2024

Others have proposed a hybrid network intrusion detection system integrating convolutional neural networks (CNN), fuzzy C-means clustering, genetic algorithm, and a bagging classifier. By hybridizing optimization techniques with deep belief networks, the method aims to enhance DDoS attack detection accuracy, speed, and scalability.

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Towards AI

FEBRUARY 3, 2024

(Left) Photo by Pawel Czerwinski on Unsplash U+007C (Right) Unsplash Image adjusted by the showcased algorithm Introduction It’s been a while since I created this package ‘easy-explain’ and published on Pypi. A few weeks ago, I needed an explainability algorithm for a YoloV8 model. The truth is, I couldn’t find anything.

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Marktechpost

MARCH 26, 2024

Deep learning models have recently gained significant popularity in the Artificial Intelligence community. In order to address these challenges, a team of researchers has introduced DomainLab, a modular Python package for domain generalization in deep learning. If you like our work, you will love our newsletter.

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Heartbeat

MAY 2, 2023

Artificial intelligence has undergone a revolution thanks to deep learning. Deep learning allows machines to learn from vast amounts of data and carry out complex tasks that were previously only considered possible by humans (like translation between languages, recognizing objects etc.).

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Towards AI

SEPTEMBER 10, 2023

What I’ve learned from the most popular DL course Photo by Sincerely Media on Unsplash I’ve recently finished the Practical Deep Learning Course from Fast.AI. So you definitely can trust his expertise in Machine Learning and Deep Learning. Luckily, there’s a handy tool to pick up Deep Learning Architecture.

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Pickl AI

AUGUST 23, 2024

Summary: This blog post delves into the importance of explainability and interpretability in AI, covering definitions, challenges, techniques, tools, applications, best practices, and future trends. For instance, if a model predicts that a loan application should be denied, explainability seeks to clarify the rationale behind this decision.

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Pickl AI

SEPTEMBER 23, 2024

Summary: This guide covers the most important Deep Learning interview questions, including foundational concepts, advanced techniques, and scenario-based inquiries. Gain insights into neural networks, optimisation methods, and troubleshooting tips to excel in Deep Learning interviews and showcase your expertise.

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Marktechpost

JUNE 16, 2024

Topological Deep Learning (TDL) advances beyond traditional GNNs by modeling complex multi-way relationships, unlike GNNs that only capture pairwise interactions. Topological Neural Networks (TNNs), a subset of TDL, excel in handling higher-order relational data and have shown superior performance in various machine-learning tasks.

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Marktechpost

APRIL 24, 2024

Explainable AI (XAI) aims to balance model explainability with high learning performance, fostering human understanding, trust, and effective management of AI partners. ELI5 is a Python package that helps debug machine learning classifiers and explain their predictions.

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The MLOps Blog

NOVEMBER 14, 2023

Deep learning models are typically highly complex. While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. The reasons for this range from wrongly connected model components to misconfigured optimizers.

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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. Introduction Deep Learning engineers are specialised professionals who design, develop, and implement Deep Learning models and algorithms.

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Towards AI

NOVEMBER 19, 2023

Photo by Pietro Jeng on Unsplash Deep learning is a type of machine learning that utilizes layered neural networks to help computers learn from large amounts of data in an automated way, much like humans do. Loss functions guide learning by measuring errors. Activation functions introduce non-linear patterns.

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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. What is Machine Learning?

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Heartbeat

FEBRUARY 21, 2024

Photo by Almos Bechtold on Unsplash Deep learning is a machine learning sub-branch that can automatically learn and understand complex tasks using artificial neural networks. Deep learning uses deep (multilayer) neural networks to process large amounts of data and learn highly abstract patterns.

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Marktechpost

AUGUST 15, 2023

Data may be viewed as having a structure in various areas that explains how its components fit together to form a greater whole. Most current deep-learning models make no explicit attempt to represent the intermediate structure and instead seek to predict output variables straight from the input.

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Marktechpost

NOVEMBER 16, 2024

Deep Learning (Adaptive Computation and Machine Learning series) This book covers a wide range of deep learning topics along with their mathematical and conceptual background. It also provides information on the different deep learning techniques used in various industrial applications.

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Marktechpost

OCTOBER 8, 2023

The researchers emphasize that this approach of explainability examines an AI’s full prediction process from input to output. The research group has already created techniques for using heat maps to demonstrate how AI algorithms make judgments. If you like our work, you will love our newsletter. We are also on WhatsApp.

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AssemblyAI

NOVEMBER 21, 2022

At the bedrock of the Deep Learning that powers incredible technologies like text-to-image models lies matrix multiplication. Regardless of the specific architecture employed, (nearly) every Neural Network relies on efficient matrix multiplication to learn and infer.

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IBM Journey to AI blog

AUGUST 9, 2024

Most generative AI models start with a foundation model , a type of deep learning model that “learns” to generate statistically probable outputs when prompted. Predictive AI blends statistical analysis with machine learning algorithms to find data patterns and forecast future outcomes.

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Pickl AI

OCTOBER 8, 2024

Summary: This blog discusses Explainable Artificial Intelligence (XAI) and its critical role in fostering trust in AI systems. One of the most effective ways to build this trust is through Explainable Artificial Intelligence (XAI). What is Explainable AI (XAI)? What is Explainable AI (XAI)?

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Heartbeat

NOVEMBER 27, 2023

Deep learning automates and improves medical picture analysis. Convolutional neural networks (CNNs) can learn complicated patterns and features from enormous datasets, emulating the human visual system. Convolutional Neural Networks (CNNs) Deep learning in medical image analysis relies on CNNs.

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Heartbeat

NOVEMBER 14, 2023

For many years, gradient-boosting models and deep-learning solutions have won the lion's share of Kaggle competitions. XGBoost is not limited to machine learning tasks, as its incredible power can be harnessed when harmonized with deep learning algorithms. 2 (2021): 522–531.

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Heartbeat

AUGUST 1, 2023

A World of Computer Vision Outside of Deep Learning Photo by Museums Victoria on Unsplash IBM defines computer vision as “a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs [1].”

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PyImageSearch

JANUARY 30, 2023

This last blog of the series will cover the benefits, applications, challenges, and tradeoffs of using deep learning in the education sector. To learn about Computer Vision and Deep Learning for Education, just keep reading. As soon as the system adapts to human wants, it automates the learning process accordingly.

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ODSC - Open Data Science

OCTOBER 17, 2023

But without a strong understanding of deep learning, you’ll have a difficult time getting the most out of the cutting-edge developments in the industry. At ODSC West this October 30th to November 2nd, you’ll build the core knowledge and skills you need with the sessions in the deep learning track , such as the ones listed below.

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Pickl AI

AUGUST 28, 2024

Summary: This comprehensive guide covers the basics of classification algorithms, key techniques like Logistic Regression and SVM, and advanced topics such as handling imbalanced datasets. It also includes practical implementation steps and discusses the future of classification in Machine Learning.

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Mlearning.ai

DECEMBER 13, 2023

Mastering Deep Learning and AI Interview Questions: What You Need to Know Image created by the author on Canva Knowledge is power, but enthusiasm pulls the switch.” Ever wondered what it takes to excel in deep learning interviews? Explain the vanishing and exploding gradient problems. said Ivern Ball.

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Heartbeat

OCTOBER 18, 2023

In this article, we embark on a journey to explore the transformative potential of deep learning in revolutionizing recommender systems. However, deep learning has opened new horizons, allowing recommendation engines to unravel intricate patterns, uncover latent preferences, and provide accurate suggestions at scale.

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Unite.AI

NOVEMBER 6, 2023

Traditional machine learning is a broad term that covers a wide variety of algorithms primarily driven by statistics. The two main types of traditional ML algorithms are supervised and unsupervised. These algorithms are designed to develop models from structured datasets. K-means Clustering. K-means Clustering.

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Heartbeat

NOVEMBER 21, 2023

Computer vision, the field dedicated to enabling machines to perceive and understand visual data, has witnessed a monumental shift in recent years with the advent of deep learning. Photo by charlesdeluvio on Unsplash Welcome to a journey through the advancements and applications of deep learning in computer vision.

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Marktechpost

JULY 22, 2023

Recent achievements in supervised tasks of deep learning can be attributed to the availability of large amounts of labeled training data. Semi-supervised learning (SSL) aims to boost model performance using labeled and unlabeled input. Yet it takes a lot of effort and money to collect accurate labels.

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Heartbeat

APRIL 23, 2023

Photo by RetroSupply on Unsplash Introduction Deep learning has been widely used in various fields, such as computer vision, NLP, and robotics. The success of deep learning is largely due to its ability to learn complex representations from data using deep neural networks. What is Epistemic Uncertainty?

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Marktechpost

MARCH 28, 2024

Deep Learning (Adaptive Computation and Machine Learning series) This book covers a wide range of deep learning topics along with their mathematical and conceptual background. It also provides information on the different deep learning techniques used in various industrial applications.

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Heartbeat

JUNE 23, 2023

However, with the advent of deep learning, researchers have explored various neural network architectures to model and forecast time series data. In this post, we will look at deep learning approaches for time series analysis and how they might be used in real-world applications. Let’s dive in!

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Pickl AI

JANUARY 15, 2023

With the speedy evolution of technologies, Machine Learning, Artificial Intelligence and Deep learning meaning might baffle you. This blog would act as a guide for you to understand the concept- What is Deep Learning?- What is Deep Learning in AI? How Deep Learning works?

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