Machine Learning Model Development Ibrahim Munir
Offering machine learning and deep learning engineering models and classifiers for all sorts of business use cases. Datasets can be built and curated if not provided before model training. Clients may supply desired metrics and performance that should be achieved by the model.
FAQs
These are simply two different ways to build a model to make some sort of predictions for you. Machine Learning is a more traditional route where computers learn patterns within the data while Deep Learning is a more complex approach that tries to emulate the way the brain thinks in order to extract meaningful information from the data and make predictions.
I can build both machine learning and deep learning models. It will typically depend on the use case and jumping on a call to determine which approach is better a fit for your specific situation.
This time it takes depends hugely on the situation. For example, a project working with a huge proprietary dataset may require weeks of cleaning, preprocessing, training, and evaluation while with a more simpler project can have all of those phases done within days.
For more niche and specific projects, it is better to provide your own dataset. However, in almost any case, a dataset can be harvested and built for a client. Datasets provided by clients will typically be better though, in most cases since they know their problem the best.
Example work
Ibrahim's other services
Contact for pricing
Tags
Python
PyTorch
scikit-learn
TensorFlow
Variational Autoencoders (VAEs)
AI Developer
AI Model Developer
ML Engineer
Service provided by
Ibrahim Munir Virginia, USA
- 3
- Followers
Machine Learning Model Development Ibrahim Munir
Contact for pricing
Tags
Python
PyTorch
scikit-learn
TensorFlow
Variational Autoencoders (VAEs)
AI Developer
AI Model Developer
ML Engineer
Offering machine learning and deep learning engineering models and classifiers for all sorts of business use cases. Datasets can be built and curated if not provided before model training. Clients may supply desired metrics and performance that should be achieved by the model.
FAQs
These are simply two different ways to build a model to make some sort of predictions for you. Machine Learning is a more traditional route where computers learn patterns within the data while Deep Learning is a more complex approach that tries to emulate the way the brain thinks in order to extract meaningful information from the data and make predictions.
I can build both machine learning and deep learning models. It will typically depend on the use case and jumping on a call to determine which approach is better a fit for your specific situation.
This time it takes depends hugely on the situation. For example, a project working with a huge proprietary dataset may require weeks of cleaning, preprocessing, training, and evaluation while with a more simpler project can have all of those phases done within days.
For more niche and specific projects, it is better to provide your own dataset. However, in almost any case, a dataset can be harvested and built for a client. Datasets provided by clients will typically be better though, in most cases since they know their problem the best.
Example work
Ibrahim's other services
Contact for pricing