COM 2023 vs Machine Learning+
Price, ratings, monetisation and update history for both apps, side by side — with what reviewers say about each.
COM 2023
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Following a successful back-in-person COM 2022, let’s continue the conversation on the theme of Climate Change and Sustainability at COM 2023 in Toronto. COM 2023 will offer curated plenaries, interactive plenary elements such as the Big Ideas session, panel discussions on decarbonizing our industries and on risks and opportunities from an insurance perspective along with the technical symposia. Technical programming will feature advanced manufacturing and materials, light metal in transportation, pressure hydrometallurgy, sustainability in pyrometallurgy, mineral processing fundamentals and integration for better outcomes from a sustainability perspective.COM promises an exciting opportunity to meet, network and learn in a dynamic environment that will emphasize industry, research and student collaborations.Plan to participate in Toronto, Ontario from Aug 21 – 24, 2023. The conference will be held at the Fairmont Royal York Hotel, steps away from Toronto’s Union Station and downtown attractions.
Machine Learning+
Master essential machine learning topics with engaging quizzes. This app covers a wide range of concepts, from algorithms and mathematical foundations to deployment and future trends, making learning enjoyable and effective for students and professionals.
- Engaging quizzes on ML topics
- Covers algorithms and math foundations
- Topics from introduction to advanced DL
- ML engineering and deployment concepts
- Future trends in machine learning
- Suitable for students and professionals
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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! Terms of Use: https://www.apple.com/legal/internet-services/itunes/dev/stdeula/ Privacy Policy: https://forwaelade.web.app/MachineLearning/privacy-policy
Screenshots
Verdict
The clearest difference is in-app purchases: COM 2023 at none against Machine Learning+'s 6. COM 2023 also leads on iOS requirement (13.0 vs 17.0). Machine Learning+'s advantage is device support. On price there is nothing between them.
Scored on Price · Rating · Positive reviews · Number of ratings · Update frequency · Ads · In-app purchases · Monetization · Best chart rank · Devices · Requires iOS
Both are free to download. Machine Learning+ sells 6 in-app purchases, starting at $7.99 per 7 days. COM 2023 asks for nothing beyond the download.
| Parameter | COM 2023 | Machine Learning+ |
|---|---|---|
| Price | Free | Free |
| Rating | — | 3.7 (3 ratings) — better |
| Positive reviews | — | 0.0% of reviews |
| Number of ratings | — | 3 — better |
| Update frequency | — | Every 3 weeks |
| Ads | — | No |
| In-app purchases | No — better | Yes |
| Monetization | — | Free with in-app purchases |
| Devices | — | iPhone, iPad — better |
| Requires iOS | 13.0 — better | 17.0 |
| Further details — not scored | ||
| Size | 29 MB | 21 MB |
| Age rating | 17+ | 4+ |
| Developer | Canadian Institute of Mining, Metallurgy and Petroleum | Forwa Elade Wunde |
In-app purchases
COM 2023
No in-app purchases
Machine Learning+
- 1 Week$7.997 Days
- 1 Month$19.991 Month
- 1 Year$29.991 Year
- 1500$1.99
- 3500$2.99
- 9000$4.99
Questions
Is COM 2023 free?
Is Machine Learning+ free?
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