Pickl AI

AUGUST 3, 2023

Introduction to Deep Learning Algorithms: Deep learning algorithms are a subset of machine learning techniques that are designed to automatically learn and represent data in multiple layers of abstraction. This process is known as training, and it relies on large amounts of labeled data.

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Dataconomy

MAY 6, 2024

Unlike traditional cloud servers that rely on CPUs, these servers leverage Graphics Processing Units (GPUs) to accelerate computational tasks. This makes them ideal for supporting complex machine learning and deep learning applications that require substantial processing power and parallel computing capabilities.

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Data Science Dojo

MAY 18, 2023

In case you were unable to attend the Future of Data and AI conference, we’ve compiled a list of all the tutorials and panel discussions for you to peruse and discover the innovative advancements presented at the Future of Data & AI conference. Check out our award-winning Data Science Bootcamp that can navigate your way.

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Smart Data Collective

DECEMBER 1, 2022

We should expect to analyze big data in the future as businesses are looking more closely to use it to remain competitive. This post outlines five current trends in big data for 2022 and beyond. Streaming analytics is a new trend in data analysis that has been gaining popularity in the past few years.

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Mlearning.ai

MAY 5, 2023

However, these early systems were limited in their ability to handle complex language structures and nuances, and they quickly fell out of favor. In the 1980s and 1990s, the field of natural language processing (NLP) began to emerge as a distinct area of research within AI.

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Data Science Connect

JULY 24, 2023

OpenAI’s Language Net: Revolutionizing Language Understanding The unveiling of Language Net by OpenAI marks a pivotal moment in AI research, redefining the state of language understanding.

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Pickl AI

APRIL 19, 2024

Continuous learning is critical to becoming an AI expert, so stay updated with online courses, research papers, and workshops. Specialise in domains like machine learning or natural language processing to deepen expertise. With dedication and perseverance, anyone can master AI and unlock its boundless potential.

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Towards AI

JULY 20, 2023

Jerome in his Study | Durer NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER The NLP Cypher | 03.14.21 Let’s talk about “Cryptonite: How I Stopped Worrying and Learned(?) (hype) PyTorch Lightning V1.2.0- LineFlow was designed to use in all deep learning… github.com Repo Cypher ?‍?

Deep Learning 87

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Dataconomy

JUNE 29, 2023

Some machine learning packages focus specifically on deep learning, which is a subset of machine learning that deals with neural networks and complex, hierarchical representations of data. Let’s explore some of the best Python machine learning packages and understand their features and applications.

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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. In a change from last year, there’s also a higher demand for those with data analysis skills as well.

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Pickl AI

AUGUST 1, 2023

Text mining is also known as text analytics or Natural Language Processing (NLP). It is the process of deriving valuable patterns, trends, and insights from unstructured textual data. Popular open-source libraries include NLTK (Natural Language Toolkit), spaCy, Gensim, sci-kit-learn, and TensorFlow.

Data Analysis 52

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Chatbots Life

APRIL 16, 2024

This is useful in natural language processing tasks. Anomaly Detection Generative models can detect anomalies in data by identifying samples that deviate significantly from the learned distribution. They can learn complex mappings between input and output variables.

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Data Science Dojo

JANUARY 13, 2023

The conference features a wide range of topics within AI, including machine learning, natural language processing, computer vision, and robotics, as well as interdisciplinary areas such as AI and law, AI and education, and AI and the arts. PAW Climate and Deep Learning World.

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Data Science Dojo

AUGUST 28, 2023

Development to production workflow LLMs Large Language Models (LLMs) represent a novel category of Natural Language Processing (NLP) models that have significantly surpassed previous benchmarks across a wide spectrum of tasks, including open question-answering, summarization, and the execution of nearly arbitrary instructions.

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ODSC - Open Data Science

MARCH 11, 2024

NLP and LLMs The NLP and LLMs track will give you the opportunity to learn firsthand from core practitioners and contributors about the latest trends in data science languages and tools, such as pre-trained models, with use cases focusing on deep learning, speech-to-text, and semantic search.

Deep Learning 52

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Towards AI

JUNE 27, 2023

For instance, today’s machine learning tools are pushing the boundaries of natural language processing, allowing AI to comprehend complex patterns and languages. However, the rapid evolution of these machine learning tools also presents a challenge for developers.

Machine Learning 97

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Mlearning.ai

JULY 17, 2023

As a data scientist, staying ahead of the curve and continuously improving your skills is essential to tackle complex challenges in the field of ML. Here we will delve into ten advanced ML techniques that every data scientist should know. GANs are widely used for tasks like image synthesis, style transfer, and data augmentation.

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Pickl AI

JANUARY 3, 2024

Geographic Variations: The average salary of a Machine Learning professional in India is ₹12,95,145 per annum. Career Advancement: Professionals can enhance earning potential by acquiring in-demand skills like Natural Language Processing, Deep Learning, and relevant certifications aligned with industry needs.

Machine Learning 52

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Smart Data Collective

JUNE 4, 2021

For academics and domain experts, R is the preferred language. it is overwhelming to learn data science concepts and a general-purpose language like python at the same time. R being a statistical language is an easier option. Exploratory Data Analysis. Deep Learning. Ensembling.

Data Science 104

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Dataconomy

APRIL 18, 2023

Understanding the basics of artificial intelligence Artificial intelligence is an interdisciplinary field of study that involves creating intelligent machines that can perform tasks that typically require human-like cognitive abilities such as learning, reasoning, and problem-solving.

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Data Science Connect

JULY 29, 2023

Leveraging the Power of AI and Deep Learning AI facial recognition relies on deep learning algorithms to analyze facial features and match them against a vast database of known individuals. Data scientists train these algorithms on large datasets to improve accuracy and reduce false positives.

Data Scientist 130

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Towards AI

AUGUST 25, 2023

Machine learning (ML) is a subset of AI that provides computer systems the ability to automatically learn and improve from experience without being explicitly programmed. Deep learning (DL) is a subset of machine learning that uses neural networks which have a structure similar to the human neural system.

Machine Learning 98

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ODSC - Open Data Science

AUGUST 15, 2023

You’ll explore the current production-grade tools, techniques, and workflows as well as explore the 8 layers of the machine learning stack. Finally, you’ll discuss a stack that offers an improved UX that frees up time for tasks that matter.

Machine Learning 52

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Dataconomy

FEBRUARY 6, 2024

These companies are using AI and ML to improve existing processes, reduce risks, and predict business performance and industry trends. When it comes to the role of AI in information technology, machine learning, with its deep learning capabilities, is the best use case.

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Dataconomy

JUNE 15, 2023

Instead of manually coding rules as in expert systems, the focus shifted to allowing computers to independently discover patterns and correlations through large-scale data analysis. Deep learning emerged as a highly promising machine learning technology for various applications.

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Data Science Connect

JULY 23, 2023

Data scientists and legal experts are closely monitoring the implications of this landmark shift in the intellectual property landscape. AI Inventor: A Novel Controversy The AI inventor in question is an advanced Generative AI system, equipped with sophisticated algorithms and deep learning capabilities.

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Dataconomy

JANUARY 24, 2024

The company is renowned for its deep understanding of machine learning and natural language processing technologies, providing practical AI solutions tailored to businesses’ unique needs. Their team of AI experts excels in creating algorithms for deep learning, predictive analytics, and automation.

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Mlearning.ai

MAY 30, 2023

RNNs contain an internal memory that enables them to capture and use context from prior inputs, in contrast to standard feedforward neural networks, which process data strictly sequentially. Speech Recognition and Natural Language Processing RNNs are frequently used for jobs involving speech recognition.

Natural Language Processing 52

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IBM Journey to AI blog

DECEMBER 15, 2023

PyTorch is an open-source AI framework offering an intuitive interface that enables easier debugging and a more flexible approach to building deep learning models. It is a popular choice among researchers and developers for rapid software development prototyping and AI and deep learning research.

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Dataconomy

MAY 25, 2023

Here are some ways AI enhances IoT devices: Advanced data analysis AI algorithms can process and analyze vast volumes of IoT-generated data. By leveraging techniques like machine learning and deep learning, IoT devices can identify trends, anomalies, and patterns within the data.

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Heartbeat

JULY 19, 2023

source: author Introduction Sentiment analysis is a rapidly growing field within the Natural Language Processing (NLP) domain, which deals with the automatic analysis and classification of emotions and opinions expressed in text. dplyr: This is a package for data manipulation and cleaning in R.

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Heartbeat

JANUARY 26, 2024

Setting Up OpenAI API The OpenAI API is a valuable resource for developers, giving them access to advanced natural language processing models to integrate into their projects. OpenAI API Capabilities The OpenAI API gives access to numerous language models, with GPT-3.5-Turbo Turbo being one of the most famous.

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Heartbeat

JUNE 5, 2023

Machine Learning Frameworks Comet integrates with a wide range of machine learning frameworks, making it easy for teams to track and optimize their models regardless of the framework they use. Ludwig Ludwig is a machine learning framework for building and training deep learning models without the need for writing code.

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Heartbeat

OCTOBER 23, 2023

Image from "Big Data Analytics Methods" by Peter Ghavami Here are some critical contributions of data scientists and machine learning engineers in health informatics: Data Analysis and Visualization: Data scientists and machine learning engineers are skilled in analyzing large, complex healthcare datasets.

Machine Learning 52

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Data Science Connect

JULY 25, 2023

As data scientists, we understand that many AI models, such as deep learning neural networks, are often considered “black boxes,” making it difficult to understand their inner workings. Ensuring AI models are transparent and can explain their decisions is crucial for building trust among users and stakeholders.

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Pickl AI

DECEMBER 4, 2023

In the realm of Data Intelligence, the blog demystifies its significance, components, and distinctions from Data Information, Artificial Intelligence, and Data Analysis. Key Components of Data Intelligence In Data Intelligence, understanding its core components is like deciphering the secret language of information.

Data Analysis 52

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Pickl AI

MARCH 7, 2024

PyTorch Functionality: PyTorch is an open-source machine learning library for Python developed by Facebook’s AI research group. Applications: PyTorch is widely used for building deep learning models, including neural networks for image classification, natural language processing, and reinforcement learning.

Data Science 52

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