ML frameworks
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Explore more → **ML frameworks**
What is ML frameworks?
ML frameworks are software libraries that provide a foundation to streamline machine learning development. They offer pre-built components, tools, and optimized functions for tasks like data preprocessing, model building, training, evaluation, and deployment. Common uses include computer vision, natural language processing, time series analysis, and predictive modeling.
What other technologies are related to ML frameworks?
ML frameworks Competitor Technologies
TensorFlow
TensorFlow is a direct competitor as it is another popular ML framework.
PyTorch
PyTorch is a direct competitor as it is another popular ML framework.
scikit-learn
Scikit-learn is a competitor, particularly for classical machine learning algorithms.
MATLAB
MATLAB provides tools for developing machine learning algorithms.
Number of organizations that mention technology
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ML frameworks Complementary Technologies
N
NLP
NLP (Natural Language Processing) is a domain where ML frameworks are heavily used.
L
LLMs
Large Language Models are models that are implemented using the framework.
d
deep learning
Deep learning is a subfield that ML frameworks facilitate.
Number of organizations that mention technology
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Which job functions commonly mention ML frameworks?
MLOps Engineer
0.2% of all MLOps Engineer jobs mention ML frameworks
View 22
jobs on Sumble
Machine Learning
0.1% of all Machine Learning jobs mention ML frameworks
View 177
jobs on Sumble
AI Engineer
0.1% of all AI Engineer jobs mention ML frameworks
View 147
jobs on Sumble
Data Scientist
0.1% of all Data Scientist jobs mention ML frameworks
View 210
jobs on Sumble
Data, Analytics & Machine Learning
573 Data, Analytics & Machine Learning jobs mention ML frameworks
View 573
jobs on Sumble
Which organizations are mentioning ML frameworks?
Standard Chartered Bank
Finance and Insurance
Google
Scientific and Technical Services
Flagship Pioneering, Inc.
Finance and Insurance
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