Building and training an Ai models

Programming & Development Math / Algorithms / Analytics

$5/hr Starting at $25

Data Collection & Preprocessing – Gathering high-quality data, cleaning it, and transforming it into a suitable format for training.
Feature Engineering – Selecting and creating relevant features that enhance the model's performance.
Model Selection – Choosing an appropriate machine learning or deep learning model based on the problem type (e.g., classification, regression, object detection).
Training the Model – Feeding the model with training data and optimizing its parameters using techniques such as gradient descent.
Evaluation & Validation – Assessing the model’s performance using test data and metrics like accuracy, precision, recall, and loss functions.
Hyperparameter Tuning – Adjusting model parameters to improve performance and avoid overfitting.
Deployment & Optimization – Integrating the trained model into real-world applications and continuously improving it based on feedback.

$5/hr Ongoing

Data Collection & Preprocessing – Gathering high-quality data, cleaning it, and transforming it into a suitable format for training.
Feature Engineering – Selecting and creating relevant features that enhance the model's performance.
Model Selection – Choosing an appropriate machine learning or deep learning model based on the problem type (e.g., classification, regression, object detection).
Training the Model – Feeding the model with training data and optimizing its parameters using techniques such as gradient descent.
Evaluation & Validation – Assessing the model’s performance using test data and metrics like accuracy, precision, recall, and loss functions.
Hyperparameter Tuning – Adjusting model parameters to improve performance and avoid overfitting.
Deployment & Optimization – Integrating the trained model into real-world applications and continuously improving it based on feedback.

AnalyticsData AnalysisData VisualizationMachine LearningMathematicsSoftware Testing

Habeba Wael