Data Science Dojo

FEBRUARY 13, 2025

Whether you’re a researcher, developer, startup founder, or simply an AI enthusiast, these events provide an opportunity to learn from the best, gain hands-on experience, and discover the future of AI. If youre serious about staying at the forefront of AI, development, and emerging tech, DeveloperWeek 2025 is a must-attend event.

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Flipboard

NOVEMBER 21, 2024

The use of time lapse systems (TLS) in In Vitro Fertilization (IVF) labs to record developing embryos has paved the way for deep-learning based computer vision algorithms to assist embryologists in their morphokinetic evaluation.

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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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Heartbeat

FEBRUARY 6, 2023

How do Object Detection Algorithms Work? There are two main categories of object detection algorithms. Two-Stage Algorithms: Two-stage object detection algorithms consist of two different stages. Single-stage object detection algorithms do the whole process through a single neural network model.

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Pickl AI

SEPTEMBER 25, 2024

Summary: This blog delves into 20 Deep Learning applications that are revolutionising various industries in 2024. From healthcare to finance, retail to autonomous vehicles, Deep Learning is driving efficiency, personalization, and innovation across sectors.

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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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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

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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Dataconomy

SEPTEMBER 25, 2024

AI integration in real-time data processing Artificial intelligence enhances real-time data processing through better comprehension with the help of advanced machine learning algorithms and analytics to act on that information. For instance, in financial markets, AI algorithms running on real-time data feed predict market fluctuations.

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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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Flipboard

JULY 1, 2023

In a paper presented earlier this year at the European Space Agency’s second NEO and Debris Detection Conference in Darmstadt, Germany, Fabrizio Piergentili and colleagues presented results of their evolutionary “genetic” algorithm to monitor the rotational motion of space debris.

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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

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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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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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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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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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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Smart Data Collective

JUNE 4, 2021

Data scientists use algorithms for creating data models. Probability is the measurement of the likelihood of events. Probability distributions are collections of all events and their probabilities. Whereas in machine learning, the algorithm understands the data and creates the logic. Semi-Supervised Learning.

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Heartbeat

MAY 23, 2023

As technology continues to improve exponentially, deep learning has emerged as a critical tool for enabling machines to make decisions and predictions based on large volumes of data. Edge computing may change how we think about deep learning. Standardizing model management can be tricky but there is a solution.

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Heartbeat

MARCH 14, 2023

By incorporating computer vision methods and algorithms into robots, they are able to view and understand their environment. Object recognition and tracking algorithms include the CamShift algorithm , Kalman filter , and Particle filter , among others.

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Dataconomy

JUNE 16, 2023

In order to prevent data loss, its system continuously monitors staff and offers event-driven security awareness training. The business’s solution makes use of AI to continually monitor personnel and deliver event-driven security awareness training in order to prevent data theft. They are knowledgeable and precise.

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ODSC - Open Data Science

APRIL 18, 2023

In particular, finance has seen some of the strongest benefits from automation and analysis thanks to AI and machine learning. Now, we’d like to go a bit deeper and specifically examine the role of machine learning in algorithmic trading, including portfolio optimization and pattern recognition.

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AWS Machine Learning Blog

MAY 16, 2024

Therefore, we decided to introduce a deep learning-based recommendation algorithm that can identify not only linear relationships in the data, but also more complex relationships. Recommendation model using NCF NCF is an algorithm based on a paper presented at the International World Wide Web Conference in 2017.

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Dataconomy

MAY 25, 2023

On the other hand, artificial intelligence is the simulation of human intelligence in machines that are programmed to think and learn like humans. 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.

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Applied Data Science

JANUARY 4, 2022

Trying to make a summary of what happened in the world of AI out of a long and vague chain of events? Reinforcement learning rethinking its practices ?‍? Four awkward moments for AI Packing a full year of exciting AI events into a single post is not easy. Hiding your 2021 resolution list under a glass of champagne?

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Smart Data Collective

NOVEMBER 1, 2020

With that being said, let’s have a closer look at how unsupervised machine learning is omnipresent in all industries. What Is Unsupervised Machine Learning? If you’ve ever come across deep learning, you might have heard about two methods to teach machines: supervised and unsupervised. Source ].

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DrivenData Labs

APRIL 10, 2024

In the Kelp Wanted challenge, participants were called upon to develop algorithms to help map and monitor kelp forests. Winning algorithms will not only advance scientific understanding, but also equip kelp forest managers and policymakers with vital tools to safeguard these vulnerable and vital ecosystems.

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Flipboard

JULY 31, 2023

Importance and Role of Datasets in Machine Learning Data is king. Algorithms are important and require expert knowledge to develop and refine, but they would be useless without data. Datasets are to machine learning what fuel is to a car: they power the entire process. Object detection is useful for many applications (e.g.,

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AWS Machine Learning Blog

JANUARY 22, 2025

On our SASE management console, the central events page provides a comprehensive view of the events occurring on a specific account. With potentially millions of events over a selected time range, the goal is to refine these events using various filters until a manageable number of relevant events are identified for analysis.

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Dataconomy

APRIL 16, 2024

These chips will be implemented across Meta’s data centers to support AI applications, notably enhancing deep learning recommendation systems that boost user engagement on its platforms. ” -Meta For instance, just last week, Google Cloud launched its inaugural Arm-based CPU during the Google Cloud Next 2024 event.

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Data Science Dojo

OCTOBER 31, 2024

Research Data Scientist Description : Research Data Scientists are responsible for creating and testing experimental models and algorithms. Key Skills: Mastery in machine learning frameworks like PyTorch or TensorFlow is essential, along with a solid foundation in unsupervised learning methods.

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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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Smart Data Collective

JUNE 22, 2023

Taking the world by storm, artificial intelligence and machine learning software are changing the landscape in many fields. Earlier today, one analysis found that the market size for deep learning was worth $51 billion in 2022 and it will grow to be worth $1.7 Amazon has a very good overview if you want to learn more.

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Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. NLP algorithms help computers understand, interpret, and generate natural language.

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Becoming Human

MARCH 16, 2023

AI began back in the 1950s as a simple series of “if, then rules” and made its way into healthcare two decades later after more complex algorithms were developed. Since the advent of deep learning in the 2000s, AI applications in healthcare have expanded. A few AI technologies are empowering drug design.

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Dataconomy

MAY 2, 2023

They design, develop, and deploy the machine learning algorithms that power everything from self-driving cars to personalized recommendations. What do machine learning engineers do? In the context of a business, machine learning engineers are responsible for creating bots that are utilized for chat purposes or data collection.

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Heartbeat

JULY 25, 2023

Introduction When it comes to practicing deep learning at home vs. industry, there’s a huge disconnect. Every course, tutorial, and YouTube video presents you with a nicely prepared dataset to feed any DL algorithm for any DL framework. And is that system in a completely different framework or programming language?

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