ODSC - Open Data Science

MARCH 10, 2025

Over the past decade, data science has undergone a remarkable evolution, driven by rapid advancements in machine learning, artificial intelligence, and big data technologies. This blog dives deep into these changes of trends in data science, spotlighting how conference topics mirror the broader evolution of datascience.

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Towards AI

FEBRUARY 1, 2024

Many of us have a functional understanding of neural networks and how they work. In this article, I’ll implement a neural network from scratch, going over different concepts like derivatives, gradient descent, and backward propagation of gradients. def f(x): return 5*x - 9xs = np.arange(-5,5,0.25)ys

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AWS Machine Learning Blog

FEBRUARY 29, 2024

In this post, we investigate of potential for the AWS Graviton3 processor to accelerate neural network training for ThirdAI’s unique CPU-based deep learning engine. In certain cases, we have even observed that our sparse CPU-based models train faster than the comparable dense architecture on GPUs.

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Unite.AI

SEPTEMBER 18, 2024

The field of artificial intelligence is evolving at a breathtaking pace, with large language models (LLMs) leading the charge in natural language processing and understanding. This family of LLMs offers enhanced performance across a wide range of tasks, from natural language processing to complex problem-solving.

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Artificial Corner

JANUARY 23, 2025

This is what I did when I started learning Python for data science. I checked the curriculum of paid data science courses and then searched all the stuff related to Python. I selected the best 4 free courses I took to learn Python for data science. All of this makes learning TensowFlow easier.

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Unite.AI

NOVEMBER 6, 2023

High-Dimensional and Unstructured Data : Traditional ML struggles with complex data types like images, audio, videos, and documents. Adaptability to Unseen Data: These models may not adapt well to real-world data that wasn’t part of their training data. Prominent transformer models include BERT , GPT-4 , and T5.

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Marktechpost

MAY 5, 2024

The course covers numerous algorithms of supervised and unsupervised learning and also teaches how to build neural networks using TensorFlow. Students learn to implement and analyze models like linear models, kernel machines, neural networks, and graphical models.

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Flipboard

DECEMBER 3, 2024

As a global leader in agriculture, Syngenta has led the charge in using data science and machine learning (ML) to elevate customer experiences with an unwavering commitment to innovation. His primary focus lies in using the full potential of data, algorithms, and cloud technologies to drive innovation and efficiency.

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IBM Journey to AI blog

DECEMBER 20, 2023

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. A semi-supervised learning model might use unsupervised learning to identify data clusters and then use supervised learning to label the clusters.

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Marktechpost

DECEMBER 12, 2024

A Deep Neural Network (DNN) is an artificial neural network that features multiple layers of interconnected nodes, also known as neurons. Each neuron processes input data by applying weights, biases, and an activation function to generate an output. pixel values of an image, numerical data).

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Pickl AI

AUGUST 14, 2024

Summary: Neural networks are a key technique in Machine Learning, inspired by the human brain. They consist of interconnected nodes that learn complex patterns in data. Understanding Neural Networks At their core, neural networks are computational models inspired by the biological neural networks that constitute animal brains.

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Pickl AI

NOVEMBER 26, 2024

Summary: Recurrent Neural Networks (RNNs) are specialised neural networks designed for processing sequential data by maintaining memory of previous inputs. They excel in natural language processing, speech recognition, and time series forecasting applications.

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ODSC - Open Data Science

NOVEMBER 28, 2024

NVIDIA’s AI Tools Suite to Aid in Accelerated Humanoid Robotics Development NVIDIA’s AI tools suite may drive developers toward complex machine learning and natural language processing solutions. In all likelihood, AI technology and humanoid robotics will progress hand in hand in the coming years. Sign up for Ai+ Training today!

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AI News

OCTOBER 15, 2024

Unsupervised machine learning systems use artificial neural networks to continue interacting with customers and retain existing customers. Speed and efficiency : Chatbots and virtual assistants can process information quicker than humans and eliminate wait times for customers.

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Heartbeat

FEBRUARY 8, 2023

Source: Author The field of natural language processing (NLP), which studies how computer science and human communication interact, is rapidly growing. By enabling robots to comprehend, interpret, and produce natural language, NLP opens up a world of research and application possibilities.

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Marktechpost

MAY 29, 2024

This article lists the top AI courses NVIDIA provides, offering comprehensive training on advanced topics like generative AI, graph neural networks, and diffusion models, equipping learners with essential skills to excel in the field. It also covers how to set up deep learning workflows for various computer vision tasks.

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IBM Journey to AI blog

JANUARY 10, 2024

Artificial intelligence (AI) refers to the convergent fields of computer and data science focused on building machines with human intelligence to perform tasks that would previously have required a human being. For example, learning, reasoning, problem-solving, perception, language understanding and more.

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ODSC - Open Data Science

JUNE 9, 2023

The 1970s introduced bell bottoms, case grammars, semantic networks, and conceptual dependency theory. In the 90’s we got grunge, statistical models, recurrent neural networks and long short-term memory models (LSTM). It uses a neural network to learn the vector representations of words from a large corpus of text.

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Towards AI

MARCH 3, 2025

Can machines understand human language? These questions are addressed by the field of Natural Language processing, which allows machines to mimic human comprehension and usage of natural language. A feedforward neural network comes next.

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ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. The chart below shows 20 in-demand skills that encompass both NLP fundamentals and broader data science expertise.

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Heartbeat

AUGUST 21, 2023

In this guide, we’ll talk about Convolutional Neural Networks, how to train a CNN, what applications CNNs can be used for, and best practices for using CNNs. What Are Convolutional Neural Networks CNN? CNNs are artificial neural networks built to handle data having a grid-like architecture, such as photos or movies.

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ODSC - Open Data Science

APRIL 3, 2023

Question Answering is the task in Natural Language Processing that involves answering questions posed in natural language. Moreover, combining expert agents is an immensely easier task to learn by neural networks than end-to-end QA. Don’t worry, you’re not alone! Haritz Puerto is a Ph.D.

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Heartbeat

SEPTEMBER 20, 2023

Pixabay: by Activedia Image captioning combines natural language processing and computer vision to generate image textual descriptions automatically. This process involves utilizing various NLP models and techniques to develop textual descriptions. Various algorithms are employed in image captioning, including: 1.

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NVIDIA Developer

JUNE 2, 2021

Applications for natural language processing (NLP) have exploded in the past decade. With the proliferation of AI assistants and organizations infusing their businesses with more interactive human-machine experiences, understanding how NLP techniques can be used to manipulate, analyze, and generate text-based data is essential.

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Unite.AI

APRIL 9, 2024

These techniques include Machine Learning (ML), deep learning , Natural Language Processing (NLP) , Computer Vision (CV) , descriptive statistics, and knowledge graphs. Key benefits include: reducing the necessity of large data science teams. Combining diverse AI techniques enables human-like decision-making.

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Heartbeat

MARCH 22, 2023

Learn NLP data processing operations with NLTK, visualize data with Kangas , build a spam classifier, and track it with Comet Machine Learning Platform Photo by Stephen Phillips — Hostreviews.co.uk Many data we analyze as data scientists consist of a corpus of human-readable text.

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NYU Center for Data Science

MARCH 1, 2023

Throughout the year, CDS community members have opportunities to attend talks by researchers in the field of data science. Organized by professors, faculty fellows, and PhD students, the speaker seminar series offers insight into topics from natural language processing to politics.

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Marktechpost

JULY 5, 2024

These courses cover foundational topics such as machine learning algorithms, deep learning architectures, natural language processing (NLP), computer vision, reinforcement learning, and AI ethics. It includes real-world projects like building neural networks and image classifiers, culminating in a completion certificate.

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Unite.AI

AUGUST 28, 2023

With advancements in deep learning, natural language processing (NLP), and AI, we are in a time period where AI agents could form a significant portion of the global workforce. Neural Networks & Deep Learning : Neural networks marked a turning point, mimicking human brain functions and evolving through experience.

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IBM Journey to AI blog

SEPTEMBER 20, 2023

Large language models (LLMs) are a class of foundational models (FM) that consist of layers of neural networks that have been trained on these massive amounts of unlabeled data. The software stack included the Red Hat OpenShift Container Platform and Red Hat OpenShift Data Science.

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ODSC - Open Data Science

MARCH 28, 2023

Designed to help you identify the sessions that best fit your interests and learning goals, the ODSC Europe 2023 tracks highlight the data science and AI fields that are helping to build the future. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

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Marktechpost

NOVEMBER 11, 2024

TensorFlow offers a flexible and scalable platform for building and training complex neural networks. TensorFlow offers a flexible and scalable platform for: Building and training complex neural networks Deploying machine learning models Natural language processing Computer vision Reinforcement learning 7.

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IBM Journey to AI blog

OCTOBER 20, 2023

These development platforms support collaboration between data science and engineering teams, which decreases costs by reducing redundant efforts and automating routine tasks, such as data duplication or extraction.

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Machine Learning Automation AI AI 225

Towards AI

APRIL 27, 2023

Understanding the Principles, Challenges, and Applications of Gradient Descent Image by Author with @MidJourney Introduction to Gradient Descent Gradient descent is a fundamental optimization algorithm used in machine learning and data science to find the optimal values of the parameters in a model.

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Marktechpost

SEPTEMBER 8, 2023

This is an entry-level tool designed for users who are just getting started with their data. Users can upload their data to the AI tool and then choose the variable they wish to predict to have Akkio construct a neural network specifically for that variable.

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ODSC - Open Data Science

APRIL 28, 2023

If a Natural Language Processing (NLP) system does not have that context, we’d expect it not to get the joke. Deep learning refers to the use of neural network architectures, characterized by their multi-layer design (i.e. His major focus has been on Natural Language Processing (NLP) technology and applications.

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ODSC - Open Data Science

AUGUST 31, 2023

The moment a cybercriminal drafts a strategy for avoiding counterfeit detectors, industry professionals reinforce them, making blockchain stronger to track and natural language processing more proficient at spotting textual inconsistencies. The relationship between AI and experts must remain strong.

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