AWS Certified Machine Learning Engineer Associate MLA-C01 Test with
Answers Rated A
Involves the extraction and transformation of variables
from raw data, such as price lists, product descriptions,
Feature Engineering
and sales volumes so that you can use features for training
and prediction
An input that machine learning (ML) models use during
Model Feature
training and inference to make predictions
A set of practices that automate and simplify machine
MLOps
learning (ML) workflows and deployments
An undesirable machine learning behavior that occurs
when the machine learning model gives accurate predic- Overfitting
tions for training data but not for new data
A machine learning (ML) technique that uses human
feedback to optimize ML models to self-learn more efl- Reinforcement Learning from Human Feedback (RLHF)
ciently.
A fully managed service that provides leading foundation
models (FMs) and a set of features for rapidly developing
Amazon Bedrock
and scaling generative artificial intelligence (AI) applica-
tions.
A type of generative artificial intelligence (AI). They pro-
duce human language instructions in response to one or Foundation Models (FMs)
more inputs (prompts).
It is a technique for improving the quality and reliability
of generative AI models by obtaining facts from external Retrieval Augmented Generation (RAG)
sources.
An extensive language model designed for text genera-
tion. It is suitable for a variety of complex, general lan-
guage applications, including open-ended text genera- Amazon Titan Text G1 - Express
tion and conversational chat, as well as support for Re-
trieval Augmented generation (RAG).
, AWS Certified Machine Learning Engineer Associate MLA-C01 Test with
Answers Rated A
It is a sequence of characters. If the model finds a stop se-
quence, it will cease creating new tokens. Ditterent models
accept ditterent sorts of characters in a stop sequence, as Stop sequences
well as varied maximum sequence lengths. They may also
permit the creation of numerous stop sequences.
A large language models (LLMs) that have been trained
to interpret massive amounts of textual data and human Text-to-text models
language.
A machine learning technology that enables machines to
Natural language processing (NLP)
understand and manipulate human language.
Utilizes a memory mechanism to store and apply infor-
mation from previous inputs. This technique makes RNNs
Recurrent neural network (RNN)
useful for sequential data and tasks like natural language
processing, speech recognition, and machine translation.
It is a deep-learning architecture that includes an encoder
Transformer
component that converts input text to embeddings.
It accepts natural language input and generate a
high-quality image that corresponds to the supplied text
description. Text-to-image models include DALL-E 2 from Text-to-image models
OpenAI, Imagen from the Google Research Brain Team,
Stable Dittusion from Stability AI, and Midjourney.
It is a deep learning architecture system that learns
through a two-step process. The first step is called forward Dittusion architecture
dittusion and second is called reverse dittusion.
It is an emerging field that focuses on developing, de-
signing, and optimizing prompts to enhance the output Prompt engineering
of LLMs for your needs.
It is a ML model that produces faster and easy to explain
Simple model
results but may not be accurate.
Answers Rated A
Involves the extraction and transformation of variables
from raw data, such as price lists, product descriptions,
Feature Engineering
and sales volumes so that you can use features for training
and prediction
An input that machine learning (ML) models use during
Model Feature
training and inference to make predictions
A set of practices that automate and simplify machine
MLOps
learning (ML) workflows and deployments
An undesirable machine learning behavior that occurs
when the machine learning model gives accurate predic- Overfitting
tions for training data but not for new data
A machine learning (ML) technique that uses human
feedback to optimize ML models to self-learn more efl- Reinforcement Learning from Human Feedback (RLHF)
ciently.
A fully managed service that provides leading foundation
models (FMs) and a set of features for rapidly developing
Amazon Bedrock
and scaling generative artificial intelligence (AI) applica-
tions.
A type of generative artificial intelligence (AI). They pro-
duce human language instructions in response to one or Foundation Models (FMs)
more inputs (prompts).
It is a technique for improving the quality and reliability
of generative AI models by obtaining facts from external Retrieval Augmented Generation (RAG)
sources.
An extensive language model designed for text genera-
tion. It is suitable for a variety of complex, general lan-
guage applications, including open-ended text genera- Amazon Titan Text G1 - Express
tion and conversational chat, as well as support for Re-
trieval Augmented generation (RAG).
, AWS Certified Machine Learning Engineer Associate MLA-C01 Test with
Answers Rated A
It is a sequence of characters. If the model finds a stop se-
quence, it will cease creating new tokens. Ditterent models
accept ditterent sorts of characters in a stop sequence, as Stop sequences
well as varied maximum sequence lengths. They may also
permit the creation of numerous stop sequences.
A large language models (LLMs) that have been trained
to interpret massive amounts of textual data and human Text-to-text models
language.
A machine learning technology that enables machines to
Natural language processing (NLP)
understand and manipulate human language.
Utilizes a memory mechanism to store and apply infor-
mation from previous inputs. This technique makes RNNs
Recurrent neural network (RNN)
useful for sequential data and tasks like natural language
processing, speech recognition, and machine translation.
It is a deep-learning architecture that includes an encoder
Transformer
component that converts input text to embeddings.
It accepts natural language input and generate a
high-quality image that corresponds to the supplied text
description. Text-to-image models include DALL-E 2 from Text-to-image models
OpenAI, Imagen from the Google Research Brain Team,
Stable Dittusion from Stability AI, and Midjourney.
It is a deep learning architecture system that learns
through a two-step process. The first step is called forward Dittusion architecture
dittusion and second is called reverse dittusion.
It is an emerging field that focuses on developing, de-
signing, and optimizing prompts to enhance the output Prompt engineering
of LLMs for your needs.
It is a ML model that produces faster and easy to explain
Simple model
results but may not be accurate.
