Artificial Intelligence in Healthcare Data is more than a comprehensive introduction to artificial intelligence and machine learning as tools in the generation and analysis of healthcare data.
Text preprocessing is an essential step in natural language processing (NLP) that involves cleaning and transforming unstructured text data to prepare it for analysis. It includes tokenization,
How does NLP differs from traditional programming or machine learning ?
Natural Processing Language is concerned more with the way computers can process, analyze, and decode human languages.
How can computer vision be applied to real-world problems and industries, such as autonomous vehicles, surveillance, medical imaging, or augmented reality?
What are the basic compenents on basic computer vision pipelines?
In computer vision, a pipeline typically consists of several stages, including image acquisition, preprocessing, feature extraction, object detection or recognition, and post-processing.
What are some popular NLP libraries and tools, such as NLTK, spaCy, or TensorFlow, and how are they used in NLP tasks?
I'm trying to upload the assignment but the file was not uploaded the file was arround 170mb
Compress the file and send
How can we preprocess and enhance images for computer vision tasks, such as resizing, cropping, denoising, or histogram equalization?
Create a function that holds image and scale size. And define a variable in the name of heights and weight. Multiply image.shape with size. On the return value cv. Reshape(image,(height, weight) , interpolation=cv.INTER_AREA) read the computer vision basics well. You may not ask the questions after you read the basics.
What are the key challenges in NLP, such as understanding the nuances of human language, ambiguity, and context?
what are the concepts need to know before learning computer vision? 'Cause I faced some difficulties while tried to understanding computer vision basics.
CONCEPTS:Linear algebra,Calculus,Probability and statistic,Image processing,Signal processing,Machine learning,Neural networks and deep learning,Feature extraction,Object detection and tracking,Evaluation metrics
谢谢你朋友
What is the intuition behind backpropagation in CNNs?
Gradient decent is behind the back propagation
How do CNNs handle multi-class classification or object detection task?
For multi-class classification, CNNs use a softmax activation function in the output layer. This function assigns a probability to each class. The class with the highest probability is then chosen as the predicted class for the input image.
Sir,could you please clarify the task assigned to us and provide more information about what actions or steps we need to take based on the given code in the resource?
from tensorflow.keras.applications.resnet50 import ResNet50 im getting error in this line. so tried to import this library. Another error popped up like the version is not satisfied. can you say which version will satisfy for this object?
Sir, shall you simply explain what we can do in our project work?
4 Reviews
8 months ago
Not bad
9 months ago
95% WORTH
9 months ago
it will be good if this topic has an example value like, if the accuracy score is closer to 1 it means it's a good classifier.
A software consultant is responsible for providing expert advice and assistance to organizations to help them implement or improve their systems.
Rakshana M
How can we preprocess and clean textual data for NLP tasks, such as removing stop words, punctuation, and performing stemming or lemmatization?