KDnuggets

DECEMBER 16, 2019

Also: Plotnine: Python Alternative to ggplot2; AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020; Moving Predictive Maintenance from Theory to Practice; 10 Free Top Notch Machine Learning Courses; Math for Programmers!

Machine Learning 135

Machine Learning Machine Learning Data Science Deep Learning 135

DrivenData Labs

MAY 12, 2025

competition, winning solutions used deep learning approaches from facial recognition tasks (particularly ArcFace and EfficientNet) to help the Bureau of Ocean and Energy Management and NOAA Fisheries monitor endangered populations of beluga whales by matching overhead photos with known individuals. For example: In the Where's Whale-do?

Algorithm 130

Algorithm Machine Learning Machine Learning Deep Learning 130

Data Science 101

JANUARY 24, 2020

Amazon Launches AutoGluon – A new open-source library which brings deep learning for images, text and tabular data to all developers. Azure SDK January 2020 Updates – The SDK now includes preview support of the Text Analytics capabilities from Cognitive Services. Language support is.Net, Java, Python, and JavaScript.

Cloud Data 129

Cloud Data Data Science Azure Machine Learning 129

Towards AI

NOVEMBER 18, 2024

A developer’s journey into creating a privacy-focused, cost-effective multi-agent system using Python and open-source LLMs. When I started learning about machine learning and deep learning in my pre-final year of undergrad in 2017–18, I was amazed by the potential of these models. This member-only story is on us.

Deep Learning 105

Deep Learning Deep Learning Data Scientist Machine Learning 105

ODSC - Open Data Science

MAY 25, 2023

sktime — Python Toolbox for Machine Learning with Time Series Editor’s note: Franz Kiraly is a speaker for ODSC Europe this June. Be sure to check out his talk, “ sktime — Python Toolbox for Machine Learning with Time Series ,” there! Welcome to sktime, the open community and Python framework for all things time series.

Machine Learning 98

Machine Learning Machine Learning Python Data Scientist 98

AWS Machine Learning Blog

DECEMBER 14, 2023

In line with this mission, Talent.com collaborated with AWS to develop a cutting-edge job recommendation engine driven by deep learning, aimed at assisting users in advancing their careers. This can significantly shorten the time needed to deploy the Machine Learning (ML) pipeline to production. session.Session().region_name

ETL 122

ETL AWS ML ML 122

AWS Machine Learning Blog

APRIL 7, 2025

Discover Llama 4 models in SageMaker JumpStart SageMaker JumpStart provides FMs through two primary interfaces: SageMaker Studio and the Amazon SageMaker Python SDK. Alternatively, you can use the SageMaker Python SDK to programmatically access and use SageMaker JumpStart models.

AWS 121

AWS Machine Learning Machine Learning ML 121

Explosion

DECEMBER 30, 2020

While 2020 hasn’t been easy for anyone, at Explosion we’ve considered ourselves relatively fortunate in this most interesting year. Mar 20: Sebastián released Typer , a library for building modern CLIs, powered by Python type hints. Here’s a look back at what we’ve been up to. Jun 21: spacy-streamlit is released!

Python 52

Python Machine Learning Machine Learning Natural Language Processing 52

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

Machine Learning Machine Learning AI AI 98

Analytics Vidhya

DECEMBER 10, 2021

Introduction Analytics Vidhya has been at the helm when it comes to publishing high-quality content since the beginning of its inception. From the latest developments to guiding people through the thorns of career, Analytics Vidhya has it all in its blog archives. And this would not have been possible without leveraging the power of the […].

Data Science 349

Data Science Analytics Analytics Data Visualization 349

Applied Data Science

OCTOBER 25, 2021

Solid theoretical background in statistics and machine learning, experience with state-of-the-art deep learning algorithms, expert command of tools for data pre-processing, database management and visualisation, creativity and story-telling abilities, communication and team-building skills, familiarity with the industry.

Data Science 130

Data Science Machine Learning Machine Learning Deep Learning 130

Towards AI

JULY 21, 2023

Deep learning and semantic parsing, do we still care about information extraction? GPT-3 hype is cool but needs fine-tuning to be anywhere near production-ready. Where are those graphs? How are downstream tasks being used in the enterprise? What about sparse networks? Why do so many AI projects fail? Are transformers the holy grail?

Natural Language Processing 98

Natural Language Processing Python Deep Learning Deep Learning 98

How to Learn Machine Learning

MAY 14, 2023

Familiarity with these subjects will enable you to understand and implement machine learning algorithms more effectively. Similarly, programming is a must-have skill for machine learning engineers. Start by learning Python and then delve into popular machine learning libraries like TensorFlow, Keras, and Scikit-learn.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

AWS Machine Learning Blog

MARCH 23, 2023

To demonstrate this, we show an example of customizing an Amazon SageMaker Scikit-learn, open sourced, deep learning container to enable a deployed endpoint to accept client-side encrypted inference requests. In this session, Feidenbaim describes two prototypes that were built in 2020. resource("s3").Bucket

AWS 123

AWS ML ML Machine Learning 123

Applied Data Science

AUGUST 2, 2021

They bring deep expertise in machine learning , clustering , natural language processing , time series modelling , optimisation , hypothesis testing and deep learning to the team. The most common data science languages are Python and R   —  SQL is also a must have skill for acquiring and manipulating data.

Data Science 130

Data Science Data Scientist ML ML 130

AWS Machine Learning Blog

FEBRUARY 23, 2023

You can use the SageMaker Python SDK to trigger a job with data parallelism with minimal modifications to the training script. Data parallelism supports popular deep learning frameworks PyTorch, PyTorch Lightening, TensorFlow, and Hugging Face Transformers. His core interests include deep learning and serverless technologies.

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AWS ML ML Machine Learning 130

Heartbeat

FEBRUARY 27, 2023

Photo by Markus Spiske on Unsplash Deep learning has grown in importance as a focus of artificial intelligence research and development in recent years. Deep Reinforcement Learning (DRL) and Generative Adversarial Networks (GANs) are two promising deep learning trends. Goodfellow, I., Pouget-Abadie, J.,

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

AWS Machine Learning Blog

JUNE 7, 2023

Starting June 7th, both Falcon LLMs will also be available in Amazon SageMaker JumpStart, SageMaker’s machine learning (ML) hub that offers pre-trained models, built-in algorithms, and pre-built solution templates to help you quickly get started with ML. The team put specific care into the craft of a high-quality trillion-token dataset.

Clustering 103

Clustering Machine Learning Machine Learning AWS 103

PyImageSearch

JANUARY 22, 2024

We estimate the parameters of the generative process ( Ho, Jain, and Abbeel, “Denoising Diffusion Probabilistic Modelsm” 2020 ). 2020) The Diffusers library, developed by Hugging Face, is an accessible tool designed for a broad spectrum of deep learning practitioners. Figure 1: Source: Ho et al. That’s not the case.

Deep Learning 67

Deep Learning Deep Learning Algorithm Python 67

AWS Machine Learning Blog

SEPTEMBER 11, 2024

In terms of resulting speedups, the approximate order is programming hardware, then programming against PBA APIs, then programming in an unmanaged language such as C++, then a managed language such as Python. In 2018, other forms of PBAs became available, and by 2020, PBAs were being widely used for parallel problems, such as training of NN.

AWS 118

AWS ML ML Clustering 118

Heartbeat

MAY 22, 2023

Training and classification Face detection from an image using Python [Source: Author] After pre-processing, we first detect the location of the face (as seen above). 2020 ) can be integrated to add greater weight to the core features. Then we detect the facial landmarks (as seen below). We pay our contributors, and we don’t sell ads.

AI 52

AI AI Deep Learning Deep Learning 52

How to Learn Machine Learning

JANUARY 10, 2023

According to fortunly , the demand for Blockchain has risen in recent years as we have obviously seen in the Crypto bull runs of 2018 and 2020. Python: The Best Programming Language To Choose For Blockchain Programming and Machine Learning. As the library of Python is very extensive, you need not rely on any external library.

Machine Learning 52

Machine Learning Machine Learning Python SQL 52

AWS Machine Learning Blog

MAY 25, 2023

in 2020 as a model where parametric memory is a pre-trained seq2seq model and the non-parametric memory is a dense vector index of Wikipedia, accessed with a pre-trained neural retriever. We package this code into Python scripts that are provided to the SageMaker Processing Job via a custom container.

AWS 98

AWS Clustering Python ML 98

Heartbeat

JUNE 6, 2023

Prerequisites To follow along with this tutorial, you will need the following: Basic knowledge of Python and deep learning. To construct the graph, we will use the NetworkX library , a Python language package that provides a convenient way to create and manipulate graphs. Richong, Z., Yongyi, M., & Xudong L.

Natural Language Processing 59

Natural Language Processing Deep Learning Deep Learning Machine Learning 59

Mlearning.ai

MARCH 9, 2023

Recent studies have demonstrated that deep learning-based image segmentation algorithms are vulnerable to adversarial attacks, where carefully crafted perturbations to the input image can cause significant misclassifications (Xie et al., Towards deep learning models resistant to adversarial attacks. 2018; Sitawarin et al.,

Deep Learning 52

Deep Learning Deep Learning Algorithm Machine Learning 52

Pickl AI

JULY 18, 2023

Develop Programming Skills Master programming languages such as Python, R, or Java, which are widely used in AI development. Gain hands-on experience in implementing algorithms and working with AI frameworks such as TensorFlow , PyTorch, or scikit-learn. billion in 2020. to reach US$ 7.8 billion by 2025 from US$ 3.1

AI 52

AI AI Machine Learning Machine Learning 52

Heartbeat

SEPTEMBER 11, 2023

Bidirectional Encoder Representations from Transformers , aka BERT, is an open-source machine learning framework for NLP. BERT is based on Transformer , a deep learning model where every output element is connected to every input element, and the weightings between them are dynamically calculated based on their connection.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

phData

AUGUST 8, 2023

AI algorithms, particularly deep learning models, involve extensive matrix operations (like dot products and matrix multiplications) and other parallelizable tasks. For example, The A100 released back in 2020 represented a significant leap forward in performance due to its Ampere microarchitecture.

AI 52

AI AI Deep Learning Deep Learning 52

Heartbeat

SEPTEMBER 13, 2023

For example, explainability is crucial if a healthcare professional uses a deep learning model for medical diagnoses. Here's an example of calculating feature importance using permutation importance with scikit-learn in Python: from sklearn.inspection import permutation_importance # Fit your model (e.g., Singh, S. &

Machine Learning 52

Machine Learning Machine Learning AI AI 52

AWS Machine Learning Blog

APRIL 18, 2023

One of the major challenges in training and deploying LLMs with billions of parameters is their size, which can make it difficult to fit them into single GPUs, the hardware commonly used for deep learning. He focuses on developing scalable machine learning algorithms.

ML 96

ML ML Deep Learning Deep Learning 96

AWS Machine Learning Blog

OCTOBER 10, 2023

Machine learning (ML), especially deep learning, requires a large amount of data for improving model performance. Federated learning (FL) is a distributed ML approach that trains ML models on distributed datasets. Customers often need to train a model with data from different regions, organizations, or AWS accounts.

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AWS ML ML Algorithm 125

Dataconomy

MAY 8, 2023

They use deep learning models to learn from large sets of images and make new ones that meet the prompts. DALL-E , which was made by OpenAI in 2020, is a more modern and more powerful AI drawing generatır. The language model for Stable Diffusion is a transformer, and it is implemented in Python.

Artificial Intelligence 194

Artificial Intelligence Artificial Intelligence AI AI 194

Heartbeat

JANUARY 5, 2024

Image by Author Large Language Models (LLMs) entered the spotlight with the release of OpenAI’s GPT-3 in 2020. Python : Great for including AI in Python-based software or data pipelines. LangChain is provided in two programming languages: Python and JavaScript. models by OpenAI. What Does LangChain Address?

AI 52

AI AI Data Pipeline Deep Learning 52

AssemblyAI

MARCH 18, 2024

Data augmentation: A technique using generative models that can create diverse and realistic variations of training data to help improve the robustness and generalization of machine learning models. Facilitate quality patient care Despite declining rates since their peak in 2020, telehealth visits remain higher than pre-pandemic levels.

AI 59

AI AI Machine Learning Machine Learning 59

DrivenData Labs

DECEMBER 13, 2022

head () Out[4]: uid latitude longitude date split 0 aabm 39.080319 -86.430867 2018-05-14 train 1 aabn 36.559700 -121.510000 2016-08-31 test 2 aacd 35.875083 -78.878434 2020-11-19 train 3 aaee 35.487000 -79.062133 2016-08-24 train 4 aaff 38.049471 -99.827001 2019-07-23 train In [5]: metadata. python train_gbm_model.py load ( f ) logger.

ML 130

ML ML Python Deep Learning 130

The MLOps Blog

JANUARY 18, 2023

Time Series forecasting using deep learning models can help retailers make more informed and strategic decisions about their operations and improve their competitiveness in the market. The idea is to leverage an accurate forecasting model that can help retailers to please their customers by having the right products at the right time.

Deep Learning 52

Deep Learning Deep Learning ML ML 52

Mlearning.ai

DECEMBER 21, 2023

The Challenge Make LLMs respond with up-to-date information Make LLMs not respond with factually inaccurate information Make LLMs aware of proprietary information Providing Context While model re-training/fine-tuning/reinforcement learning are options that solve the aforementioned challenges, these approaches are time-consuming and costly.

Database 94

Database AI AI Machine Learning 94