Transfer Learning Professional Certification – ITRONIX SOLUTIONS
Get Transfer Learning Certificate from Itronix Solutions which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.
Exam Details :
- Format: Multiple Choice Question
- Questions: 10
- Passing Score: 8/10 or 80%
- Language: English
Transfer learning is a machine learning technique where a model trained on one task is re-purposed on a second related task.
True
False
Which is the common approach that can use transfer learning on your own predictive modeling problems.
Develop Model Approach
Pre-trained Model Approach
All of the above
_ is an approach in deep learning (and machine learning) where knowledge is transferred from one model to another.
Machine Learning
Transfer Learning
Deep Learning
Artificial Learning
Which is not a type of transfer of learning?
Domain adaptation
Domain confusion
Multitask learning
Hot-shot learning
_ Transfer Learning requires the source and target domains to be the same, though the specific tasks the model is working on are different.
Inductive
Transductive
Unsupervised
None of the above
_ Transfer learning approaches are developed and proposed to handle situations where the domains are of the same feature space.
Hetrogeneous
Homogeneous
Hypergeneous
Supergeneous
Transfer learning is so common that it is rare to train a model for an __ related tasks from scratch.
text
mysql
json
image or natural language processing
The _ transfer learning approaches transfer the knowledge at the model/parameter level.
recurrent-based
hyperperameter-based
parameter-based
sequential-based
In __ sharing, the model is expected to be close to the already learned features and is usually penalized if its weights deviate significantly from a given set of weights.
heavy weight
soft weight
light weight
hard weight
Which of these are pre-trained models you can use For NLP tasks?
Word2Vec
GloVe
FastText
All of the above
