Mazhar Javed isn't taking new orders for this project right now. Here are some similar projects to explore.
You will get Feature Extraction MRI images deep learning
Project details
Feature extraction features in the data frame
The method should be novel like Stacking weighted averaging through Hierarchical Spatial Attention Fusion (HSAF), detail is at the end.
In every combination shows novelty in the staking of the pre-trained model, does differently like attention involvement, in a weighted average to get optimal features by some objective function than in hierarchical also do different way outs.
The method should be novel like Stacking weighted averaging through Hierarchical Spatial Attention Fusion (HSAF), detail is at the end.
In every combination shows novelty in the staking of the pre-trained model, does differently like attention involvement, in a weighted average to get optimal features by some objective function than in hierarchical also do different way outs.
Machine Learning Tools
Amazon SageMaker, Keras, Python, Python Scikit-LearnWhat's included
| Service Tiers |
Starter
$50
|
Standard
$60
|
Advanced
$80
|
|---|---|---|---|
| Delivery Time | 8 days | 1 day | 1 day |
Number of Revisions | 1 | 0 | 0 |
Number of Model Variations | 3 | ||
Model Validation/Testing | - | - | |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - | - |
About Mazhar Javed
Expert Data Scientist | AI Research Scientist | Trainer| AI Consultant
Lahore, Pakistan - 7:57 am local time
My main areas of expertise are:
-Python 3.10 , R Language, Keras
-Medical Image Analytics
-Healthcare
-Data Engineering: Handling missing
noisy data, Identifying Outlier Detection, and Data normalization ( Numpy, Pandas,
-Data Visualization: Matplotlib, seaborn, Tableau ( all kinds of plots for Data Exploration analysis and evaluation )
-Machine learning: Supervised, unsupervised, regression, ensemble, boosting models fully concept and expertise in code as well (Scikit learn)
-Natural language processing: can do Text preprocessing, TF-IDF, Naive Bayes model ( NLTK, Text2Blob ), Attention , Transformers, Language Models , Large Language Models
-Time Series Analysis
-Deep Learning: Commands in all deep learning models classification, segmentation, object detection: CNN, CNN architectures, LSTM, auto-encoders ( Keras, Tensor flow), Medical images, Vision Transformers, Generative AI
-Big data: SPARK, Data bricks, data lakes, snowflake, sage maker
Deployment: MLOps: Ml flow, Dockers, Flask
Steps for completing your project
After purchasing the project, send requirements so Mazhar Javed can start the project.
Delivery time starts when Mazhar Javed receives requirements from you.
Mazhar Javed works on your project following the steps below.
Revisions may occur after the delivery date.
Feature Learning