ODSC - Open Data Science

OCTOBER 24, 2023

In addition, all evaluations were performed using cross-validation: splitting the real data into training and validation sets, using the training data only for synthetization, and the validation set to assess performance. Interested in attending an ODSC event? Learn more about our upcoming events here.

Data Science 98

Data Science Cross Validation Algorithm Machine Learning 98

Pickl AI

FEBRUARY 17, 2025

It uses predictive modelling to forecast future events and adaptiveness to improve with new data, plus generalization to analyse fresh data. Summary: Machine Learning’s key features include automation, which reduces human involvement, and scalability, which handles massive data.

Machine Learning 52

Machine Learning Machine Learning Supervised Learning ML 52

Ocean Protocol

NOVEMBER 28, 2024

Participants used historical data from past Mexican Grand Prix events and insights from the 2024 F1 season to create machine-learning models capable of predicting key race elements. Firepig refined predictions using detailed feature engineering and cross-validation.

Cross Validation 85

Cross Validation Decision Trees Data Scientist Data Science 85

AWS Machine Learning Blog

MAY 24, 2023

Third-party validation We integrate the solution with third-party providers (via API) to validate the extracted information from the documents, such as personal and employment information. You can use the prediction to trigger business rules in relation to underwriting decisions.

AWS 95

AWS ML ML AI 95

DrivenData Labs

MARCH 28, 2023

Training data was splited into 5 folds for cross validation. latitude and longitude) Incorporating elevation and land cover information Continue experimenting with other loss functions Cross-validation Potentially better architectures (e.g. Outliers were replaced by the lower or upper limitations. I am a Ph.D.

Machine Learning 130

Machine Learning Machine Learning Cross Validation Deep Learning 130

Heartbeat

FEBRUARY 20, 2023

Additionally, I will use StratifiedKFold cross-validation to perform multiple train-test splits. #defining X and y X = df.drop(['target'], axis=1) y = df['target'] Now, we can move to testing and fitting an algorithm, then exporting the model and registering it to the Model Registry.

Cross Validation 87

Cross Validation ML ML Machine Learning 87

AWS Machine Learning Blog

SEPTEMBER 29, 2023

Assessing and mitigating damage – Finally, crop segmentation can be used to quickly and accurately identify areas of crop damage in the event of a natural disaster, which can help prioritize relief efforts. Planet Labs PBC undertakes no obligation to update forward-looking statements to reflect future events or circumstances.

Machine Learning 139

Machine Learning Machine Learning ML ML 139

DrivenData Labs

JANUARY 11, 2023

1D vs. 2D deep learning : The first-place winner used a 1D CNN transformer whose output feeds into a 1D event detection model, and a 2D CNN whose output feeds into a 2D event detection model, while the second-place winner ensembled 13 different 2D CNNs with different preprocessing methods.

Deep Learning 130

Deep Learning Deep Learning Data Science Machine Learning 130

DrivenData Labs

APRIL 10, 2024

We take a gap year to participate in AI competitions and projects, and organize and attend events. At the time of selecting competitions, this was the most attractive in terms of sustainability, image segmentation being a new type of challenge for this team, and having a topic that would be easy to explain and visualize at events.

Deep Learning 130

Deep Learning Deep Learning Machine Learning Machine Learning 130

Mlearning.ai

FEBRUARY 10, 2024

These mathematical domains serve as the crucial framework for comprehending patterns in data, allowing us to make highly accurate forecasts about future events. It serves as a fundamental principle in probability theory, illustrating how the likelihood of an event or hypothesis evolves as additional information is acquired.

Algorithm 52

Algorithm Decision Trees Cross Validation Machine Learning 52

Heartbeat

OCTOBER 31, 2023

Cross-validation is recommended as best practice to provide reliable results because of this. Output: We can observe a rise in model performance from 82.2% by iterating through various settings for the number of estimators. In this instance, we observe a 13.3% improvement in wine type identification precision.

Decision Trees 52

Decision Trees Deep Learning Deep Learning Cross Validation 52

Ocean Protocol

AUGUST 9, 2024

Luca’s visualizations showed significant revenue declines during major reforms and economic events. He used the Prophet model and conducted thorough cross-validation, achieving mean squared error (MSE) values as low as 0.0007 for short-term forecasts. for labor unions.

AI 45

AI AI Cross Validation Data Scientist 45

Ocean Protocol

FEBRUARY 1, 2024

After that, you can train your model, tune its parameters, and validate its performance using metrics like RMSE, MAE, or MAPE. It’s also a good practice to perform cross-validation to assess the robustness of your model. When implementing these models, you’ll typically start by preprocessing your time series data (e.g.,

Exploratory Data Analysis 52

Exploratory Data Analysis Data Science Cross Validation Machine Learning 52

Heartbeat

AUGUST 29, 2023

Cross-validation : Cross-validation is a method for assessing how well a model performs when applied to fresh data. Make use of cross-validation : Before deploying your model, cross-validation can help you find overfitting and generalization issues.

Deep Learning 52

Deep Learning Deep Learning Cross Validation Data Quality 52

DataRobot Blog

DECEMBER 20, 2022

Monitoring models in production and continuously learning in an automated way, so being prepared for real estate market shifts or unexpected events. For example, the model produced a RMSLE (Root Mean Squared Logarithmic Error) Cross Validation of 0.0825 and a MAPE (Mean Absolute Percentage Error) Cross Validation of 6.215.

AI 59

AI AI Cross Validation Machine Learning 59

Heartbeat

MARCH 27, 2023

You can also sign up to receive our weekly newsletter ( Deep Learning Weekly ), check out the Comet blog , join us on Slack , and follow Comet on Twitter and LinkedIn for resources, events, and much more that will help you build better ML models, faster.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

DECEMBER 16, 2024

Split the Data: Divide your dataset into training, validation, and testing subsets to ensure robust evaluation. Cross-validation: Implement cross-validation techniques to assess how well your model generalizes to unseen data. This is vital for agriculture, disaster management, and event planning.

AI 52

AI AI Machine Learning Machine Learning 52

Heartbeat

OCTOBER 23, 2023

By analyzing historical data and utilizing predictive machine learning algorithms like BERT, ARIMA, Markov Chain Analysis, Principal Component Analysis, and Support Vector Machine, they can assess the likelihood of adverse events, such as hospital readmissions, and stratify patients based on risk profiles.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Big Data Analytics 52

Mlearning.ai

MAY 23, 2023

What is Cross-Validation? Cross-Validation is a Statistical technique used for improving a model’s performance. Perform cross-validation of the model. Perform K-fold cross-validation correctly: Cross-Validation needs to be applied properly while using over-sampling.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Heartbeat

DECEMBER 19, 2023

You can also sign up to receive our weekly newsletter ( Deep Learning Weekly ), check out the Comet blog , join us on Slack , and follow Comet on Twitter and LinkedIn for resources, events, and much more that will help you build better ML models, faster.

Deep Learning 52

Deep Learning Deep Learning Algorithm Machine Learning 52

Heartbeat

JUNE 14, 2023

Cross Validated] Editor’s Note: Heartbeat is a contributor-driven online publication and community dedicated to providing premier educational resources for data science, machine learning, and deep learning practitioners. Advances in Neural Information Processing Systems 33 (2020): 15288–15299. [10] 10] Nixon, Jeremy, et al.

Deep Learning 59

Deep Learning Deep Learning Support Vector Machines Machine Learning 59

Pickl AI

SEPTEMBER 12, 2024

Cross-Validation: A model evaluation technique that assesses how well a model will generalise to an independent dataset. Joint Probability: The probability of two events co-occurring, often used in Bayesian statistics and probability theory.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

DECEMBER 12, 2024

This feature makes it ideal for datasets with class imbalances, such as fraud detection or rare event prediction. Monitor Overfitting : Use techniques like early stopping and cross-validation to avoid overfitting. This ensures better predictions for rare events. Why is XGBoost Ideal for Imbalanced Datasets?

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Pickl AI

AUGUST 9, 2024

Students should understand the concepts of event-driven architecture and stream processing. Model Evaluation Techniques for evaluating machine learning models, including cross-validation, confusion matrix, and performance metrics. Knowledge of RESTful APIs and authentication methods is essential.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

The MLOps Blog

DECEMBER 7, 2022

This is a relatively straightforward process that handles training with cross-validation, optimization, and, later on, full dataset training. Event trigger At this moment, we’re implementing it to notify processing job changes.

ML 52

ML ML AWS ETL 52

Pickl AI

OCTOBER 15, 2024

They identify patterns in existing data and use them to predict unknown events. Model Validation Model validation is a critical step to evaluate the model’s performance on unseen data. Predictive Models Predictive models are designed to forecast future outcomes based on historical data.

Decision Trees 52

Decision Trees Hypothesis Testing Clustering Data Analysis 52

Heartbeat

MAY 29, 2023

Use a representative and diverse validation dataset to ensure that the model is not overfitting to the training data. Use a separate testing dataset to assess the generalization ability of the model and its effectiveness in solving the intended task in the real-world scenario.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78

DrivenData Labs

MAY 1, 2025

Top solvers from Phase 2 demonstrate algorithmic approaches on diverse datasets and share their results at an innovation event. This event uses data from the Mexican Health and Aging Study (MHAS), which is an additional motivator since I was born there. Phase 3 [Put IT All Together!] Participants competed in two modeling tracks.

Decision Trees 147

Decision Trees Clustering Algorithm Machine Learning 147

Mlearning.ai

JANUARY 29, 2024

According to the CDC more than 1 million individuals visit emergency departments for adverse drug events each year in the United States. ADRs can range from mild symptoms, such as nausea or dizziness, to more serious or life-threatening events, such as anaphylaxis(severe allergic reaction) or organ damage.

Decision Trees 52

Decision Trees Data Science Exploratory Data Analysis Data Analysis 52

Dataconomy

SEPTEMBER 1, 2023

Techniques like cross-validation and robust evaluation methods are crucial. By leveraging real-time data, hybrid models can provide timely insights, potentially preventing adverse cardiac events and improving patient outcomes. The class distribution in heart disease datasets can be imbalanced, with fewer positive cases.

Decision Trees 195

Decision Trees Machine Learning Machine Learning Support Vector Machines 195