Machine Learning+
Regression, Clustering & more
Free · In-App Purchases · Designed for iPad
Master all essential concepts in Machine Learning with our App! Learn, practice, and excel with interactive quizzes on the go. Download now and ace your skills!
Master all essential topics in Machine Learning exam with Fun and Engaging Quizzes!
Dive into the world of Machine Learning with our comprehensive quiz app, designed to boost your knowledge, confidence, and skills. Whether you're a student, practitioner, or just exploring the field, this app is your ultimate companion for learning and growth.
Topics Covered:
Introduction to Machine Learning:
-Definition, scope and applications in engineering domains
-Types of machine learning (supervised, unsupervised, reinforcement)
Mathematical Foundations:
-Linear algebra essentials
-Probability and statistics
-Calculus for optimization
Data Engineering for ML:
-Data collection, cleaning, and preprocessing
-Feature engineering and selection
-Handling missing and imbalanced data
Supervised Learning Algorithms:
-Regression models
-Classification techniques
-Evaluation metrics
Unsupervised Learning Algorithms:
-Clustering methods (k-means, DBSCAN, hierarchical)
-Dimensionality reduction (PCA, t-SNE)
-Applications in anomaly detection
Neural Networks and Deep Learning:
-Perceptrons and MLPs
-Activation functions
-Backpropagation
Advanced Deep Learning Architectures:
-Convolutional Neural Networks (CNNs)
-Recurrent Neural Networks (RNNs), LSTMs, GRUs
-Transformers and attention mechanisms
Reinforcement Learning:
-Markov decision processes
-Value-based methods (Q-learning)
-Policy-based methods
Model Training and Optimization:
-Gradient descent and variants (SGD, Adam, RMSProp)
-Hyperparameter tuning
-Regularization techniques
Model Evaluation and Validation:
-Cross-validation methods
-Bias-variance trade-off
-Overfitting and underfitting
ML Engineering and Deployment:
-Model pipelines and MLOps
-Deployment strategies (cloud, edge, embedded systems)
-CI/CD for ML
Scalable Machine Learning:
-Distributed training (Hadoop, Spark MLlib)
-Parallelization strategies
-GPU/TPU acceleration
Interpretability and Explainability:
-SHAP, LIME, feature importance
-Explainable AI in engineering applications
-Ethical considerations
ML for Engineering Applications:
-Predictive maintenance
-Computer vision for defect detection
-Control systems and optimization
Future Trends in Machine Learning:
-Federated learning
-Self-supervised learning
-AI safety and ethical AI engineering
Who is it for?
- Engineering students preparing for exam.
- Professionals brushing up on their knowledge.
- Anyone interested in understanding Machine Learning concepts.
Download now and make learning Machine Learning enjoyable and effective!
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Information
- Seller
- Forwa Elade Wunde
- Size
- 27.4 MB
- Category
- Education
- Compatibility
Requires iOS 17.0 or later.
- iPhone
Requires iOS 17.0 or later. - iPad
Requires iPadOS 17.0 or later. - Mac
Requires macOS 14.0 or later and a Mac with Apple M1 chip or later. - Apple Vision
Requires visionOS 1.0 or later.
- Languages
- English
- Age Rating
4+
- 4+
- Contains
User-Generated Content
- In-App Purchases
Yes
- 9000 USD 4.99
- 3500 USD 2.99
- 1500 USD 1.99
- 1 Week USD 7.99
- 1 Month USD 19.99
- 1 Year USD 29.99
- Copyright
- © Forwa Elade