Mlearning.ai

JUNE 14, 2023

Deploy LLMs in production Deploy Model Azure —  Use endpoints for inference — Azure Machine Learning | Microsoft Learn AWS + Huggingface —  Exporting ? Transformers (huggingface.co) Training Sentiment Model Using BERT and Serving it with Flask API — YouTube 5.

Natural Language Processing 52

Natural Language Processing ML ML Support Vector Machines 52

Pickl AI

JULY 12, 2024

Support Vector Machines (SVM) SVMs classify data points by finding the optimal hyperplane that maximises the margin between classes. Popular models include decision trees, support vector machines (SVM), and neural networks. classification, regression) and data characteristics.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

NOVEMBER 28, 2024

Support Vector Machines (SVM) SVMs are powerful classifiers that separate data into distinct categories by finding an optimal hyperplane. Cloud platforms like AWS , Google Cloud Platform (GCP), and Microsoft Azure provide managed services for Machine Learning, offering tools for model training, storage, and inference at scale.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

DagsHub

APRIL 21, 2024

Scikit-learn provides a consistent API for training and using machine learning models, making it easy to experiment with different algorithms and techniques. SageMaker offers a comprehensive set of tools and capabilities for the entire machine-learning lifecycle.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

ODSC - Open Data Science

JANUARY 7, 2025

From development environments like Jupyter Notebooks to robust cloud-hosted solutions such as AWS SageMaker, proficiency in these systems is critical. Core Machine Learning Algorithms Core machine learning algorithms remain foundational for data science workflows.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Dataconomy

MARCH 13, 2023

Here are some of the essential tools and platforms that you need to consider: Cloud platforms Cloud platforms such as AWS , Google Cloud , and Microsoft Azure provide a range of services and tools that make it easier to develop, deploy, and manage AI applications.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence Natural Language Processing Algorithm 98

Pickl AI

NOVEMBER 18, 2024

spam detection), you might choose algorithms like Logistic Regression , Decision Trees, or Support Vector Machines. Cloud Platforms for Machine Learning Cloud platforms like AWS, Google Cloud, and Microsoft Azure provide powerful infrastructures for building and deploying Machine Learning Models.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52