2013, ML and Python - Data Science Current

sktime?—?Python Toolbox for Machine Learning with Time Series

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

Machine Learning Machine Learning Python Data Scientist

Generate financial industry-specific insights using generative AI and in-context fine-tuning

AWS Machine Learning Blog

NOVEMBER 12, 2024

In entered the Big Data space in 2013 and continues to explore that area. He is actively working on projects in the ML space and has presented at numerous conferences including Strata and GlueCon. He works with strategic customers who are using AI/ML to solve complex business problems. Arghya Banerjee is a Sr.

SQL

SQL AWS AI AI

Accelerate time to business insights with the Amazon SageMaker Data Wrangler direct connection to Snowflake

AWS Machine Learning Blog

JUNE 23, 2023

Amazon SageMaker Data Wrangler is a single visual interface that reduces the time required to prepare data and perform feature engineering from weeks to minutes with the ability to select and clean data, create features, and automate data preparation in machine learning (ML) workflows without writing any code.

ML

ML ML Database AWS

Webinars

How to Achieve High-Accuracy Results When Using LLMs

MORE WEBINARS

16 Companies Leading the Way in AI and Data Science

ODSC - Open Data Science

FEBRUARY 28, 2023

To deliver on their commitment to enhancing human ingenuity, SAS’s ML toolkit focuses on automation and more to provide smarter decision-making. Plotly In the time since it was founded in 2013, Plotly has released a variety of products including Plotly.py, which, along with Plotly.r,

Data Science

Data Science Machine Learning Machine Learning AI

How to Predict Harmful Algal Blooms Using LightGBM and Satellite Imagery

DrivenData Labs

DECEMBER 13, 2022

agg ( min_date = ( "date" , min ), max_date = ( "date" , max )) Out[8]: min_date max_date split test 2013-01-08 2021-12-29 train 2013-01-04 2021-12-14 In [9]: # what years are in the data? The severity levels are: severity Density range (cells per mL) 1 10,000,00)" , } } ). python train_gbm_model.py

ML

ML ML Python Deep Learning

Containerization of Machine Learning Applications

Heartbeat

DECEMBER 27, 2023

However, the emergence of the open-source Docker engine by Solomon Hykes in 2013 accelerated the adoption of the technology. The machine learning (ML) lifecycle defines steps to derive values to meet business objectives using ML and artificial intelligence (AI). Prerequisite Python 3.8 What is Docker? Docker installation.

Machine Learning

Machine Learning Machine Learning Python ML

Time Series Forecasting with XGBoost and LightGBM: Predicting Energy Consumption with Lag Features

Mlearning.ai

AUGUST 6, 2023

We can plot these with the help of the `plot_pacf` function of the statsmodels Python package: [link] Partial autocorrelation plot for 12 lag features We can clearly see that the first 9 lags possibly contain valuable information since they’re out of the bluish area.

Python

Python Algorithm AI AI

Deep Learning for NLP: Word2Vec, Doc2Vec, and Top2Vec Demystified

Mlearning.ai

APRIL 1, 2023

It was first introduced in 2013 by a team of researchers at Google led by Tomas Mikolov. Image taken from Top2Vec: Distributed Representation of Topic Python Code We will now provide some Python code examples for training Word2Vec, Doc2Vec, and Top2Vec models. Representation of Topic Vector.

Deep Learning

Deep Learning Deep Learning Natural Language Processing Clustering

Train An Emotion Recognition Model Using Multiple Datasets-Part 1

Mlearning.ai

JUNE 21, 2023

FER, Facial Expression Recognition, is an open-source dataset released in 2013. Instead, it utilizes Python Hooks to stream datasets that are already in the remote repository. BECOME a WRITER at MLearning.ai // FREE ML Tools // Clearview AI Mlearning.ai What is the FER dataset? If you have any questions, feel free to reach out.

Deep Learning

Deep Learning Deep Learning ML ML

Robustness of a Markov Blanket Discovery Approach to Adversarial Attack in Image Segmentation: An…

Mlearning.ai

MARCH 9, 2023

2013; Goodfellow et al., We implemented the MBD approach using the Python programming language, with the scikit-learn and NetworkX libraries for feature selection and structure learning, respectively. We also ensured that the selected images were not part of the training set for the MBD model, to avoid any bias in the results.

Deep Learning

Deep Learning Deep Learning Machine Learning Machine Learning

An Exploratory Look at Vector Embeddings

Mlearning.ai

JULY 31, 2023

Dosovitskiy, A., Kolesnikov, A., Weissenborn, D., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Uszkoreit, J., and Houlsby, N., An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. Available from: [link]. Mikolov, T., Corrado, G., and Dean, J., Efficient Estimation of Word Representations in Vector Space.

Deep Learning

Deep Learning Deep Learning Supervised Learning Algorithm

Meet the winners of the Unsupervised Wisdom Challenge!

DrivenData Labs

DECEMBER 7, 2023

In this challenge, solvers submitted an analysis notebook (in R or Python) and a 1-3 page executive summary that highlighted their key findings, summarized their approach, and included selected visualizations from their analyses. Solution format. Guiding questions. There was no one common methodological pattern among the top solutions.

Natural Language Processing

Natural Language Processing Clustering Data Science Data Analysis

How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Flipboard

NOVEMBER 24, 2023

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning. Clay Elmore is an AI/ML Specialist Solutions Architect at AWS.

Database

Database AWS ETL SQL

Top Data Science Facts You Should Know

Pickl AI

MARCH 7, 2025

High Demand for Data Scientists: Data Science roles have grown over 250% since 2013, with salaries reaching $153k/year. Job Growth: Data Science roles have grown by 256% since 2013 , with a projected growth rate of 36% between 2023 and 2033. Example: Netflix uses ML to recommend shows based on viewing history.

Data Science

Data Science Machine Learning Machine Learning Data Scientist

Top Big Data Tools Every Data Professional Should Know

Pickl AI

FEBRUARY 23, 2025

Ease of Use : Supports multiple programming languages including Python, Java, and Scala. Machine Learning Integration : Built-in ML capabilities streamline model development and deployment. Statistics: Tableau has been recognized as a leader in the Gartner Magic Quadrant for Analytics and Business Intelligence Platforms since 2013.

Big Data

Big Data Big Data Apache Hadoop Apache Kafka

Data Science Current

sktime?—?Python Toolbox for Machine Learning with Time Series

Generate financial industry-specific insights using generative AI and in-context fine-tuning

Webinars

Trending Sources

Accelerate time to business insights with the Amazon SageMaker Data Wrangler direct connection to Snowflake

Webinars

16 Companies Leading the Way in AI and Data Science

How to Predict Harmful Algal Blooms Using LightGBM and Satellite Imagery

Containerization of Machine Learning Applications

Time Series Forecasting with XGBoost and LightGBM: Predicting Energy Consumption with Lag Features

Deep Learning for NLP: Word2Vec, Doc2Vec, and Top2Vec Demystified

Train An Emotion Recognition Model Using Multiple Datasets-Part 1

Robustness of a Markov Blanket Discovery Approach to Adversarial Attack in Image Segmentation: An…

An Exploratory Look at Vector Embeddings

Meet the winners of the Unsupervised Wisdom Challenge!

How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Top Data Science Facts You Should Know

Top Big Data Tools Every Data Professional Should Know

Stay Connected