What powers self-driving cars like Tesla?
Anonymous Quiz
15%
A. Motion sensors only
12%
B. Rule-based software
72%
C. Deep learning models
1%
D. Manual programming
👍2
What do Siri and Alexa use to understand human speech?
Anonymous Quiz
1%
A. Spreadsheets
4%
B. SQL queries
93%
C. Natural Language Processing
2%
D. Keyboard shortcuts
🔥2
How does AI assist in agriculture?
Anonymous Quiz
3%
A. Driving tractors
3%
B. Forecasting sales
93%
C. Predicting weather and monitoring crops
1%
D. Planting seeds manually
👏2
In media, what is AI used for?
Anonymous Quiz
12%
A. Film projection
82%
B. Script writing and music creation
4%
C. Ticket selling
1%
D. Popcorn ordering
🔥3
What’s one cybersecurity use of AI?
Anonymous Quiz
3%
A. Installing antivirus
7%
B. Writing code
88%
C. Detecting real-time threats
3%
D. Changing user passwords
👏3
The 5 FREE Must-Read Books for Every AI Engineer
1. Practical Deep Learning
A hands-on course using Python, PyTorch, and fastai to build, train, and deploy real-world deep learning models through interactive notebooks and applied projects.
2. Neural Networks and Deep Learning
An intuitive and code-rich introduction to building and training deep neural networks from scratch, covering key topics like backpropagation, regularization, and hyperparameter tuning.
3. Deep Learning
A comprehensive, math-heavy reference on modern deep learning—covering theory, core architectures, optimization, and advanced concepts like generative and probabilistic models.
4. Artificial Intelligence: Foundations of Computational Agents
Explains AI through computational agents that learn, plan, and act, blending theory, Python examples, and ethical considerations into a balanced and modern overview.
5. Ethical Artificial Intelligence
Explores how to design safe AI systems by aligning them with human values and preventing issues like self-delusion, reward hacking, and unintended harmful behavior
✅ Double Tap ❤️ For More
1. Practical Deep Learning
A hands-on course using Python, PyTorch, and fastai to build, train, and deploy real-world deep learning models through interactive notebooks and applied projects.
2. Neural Networks and Deep Learning
An intuitive and code-rich introduction to building and training deep neural networks from scratch, covering key topics like backpropagation, regularization, and hyperparameter tuning.
3. Deep Learning
A comprehensive, math-heavy reference on modern deep learning—covering theory, core architectures, optimization, and advanced concepts like generative and probabilistic models.
4. Artificial Intelligence: Foundations of Computational Agents
Explains AI through computational agents that learn, plan, and act, blending theory, Python examples, and ethical considerations into a balanced and modern overview.
5. Ethical Artificial Intelligence
Explores how to design safe AI systems by aligning them with human values and preventing issues like self-delusion, reward hacking, and unintended harmful behavior
✅ Double Tap ❤️ For More
❤2