Bilgi Teknolojisi Ödev Yardımı
Bilgi teknolojisi atama yardımı, kullanıcılara en ileri bilim ve teknoloji hakkında çok yüksek kalitede bilgi sağlayabilir. Çok detaylı kategorize edilmiş bilgi verileri vardır ve yazılımın kendisinin bunları kullanma izni yoktur, böylece herkes teknolojiden sonuna kadar yararlanabilir.
Alışılmışın dışında teknoloji ve yaşam için de mükemmel bir içerik organizasyonudur. İlginç ve profesyonel içerik üretmek için kullanıcıları ve markaları birbirine bağlar. Teknik bilgiler, derinlemesine incelemeler, beceri ipuçları ve ürün deneyimleri vb. içerir. Grafik, video ve bilgilendirici reklam içerik formatlarına sahiptir ve başlıca yeni medya platformlarını kapsar.
- __ are programs used by many people to accomplish frequently performed tasks. a. Software-purpose applications b. General-purpose applications c. Multi-purpose applications d. All-purpose applications
- __ Retrieves the next program instruction from memory a. POST b. EXECUTE c. DECODE d. FETCH
- __ is not located in the system unit Select one: a. ROM b. CD c. CPU d. FAN Clear my choice
- 15. Which activation function outputs values between 4 and 1? a. Tanh b. ReLU c. Sigmoid d. Softmax 16. Which of the following is a state -of-the-art G GPU/hardware accelerator or for deep learning? a. Raspberry Pi b. Arduino c. H100 d. Intel Core 17 17. What distinguishes AGI from Narrow Al? a. AGl is limited to a single domain b. AGl only works with supervised learning c. AGI can solve a wide range of tasks like humans d. AGI relies solely on rule-based systems 18. What is the Perceptron in the context of neural networks? a. The simplest form of a neural network with a single layer b. A complex neural network with multiple hidden layers c. A type of convolutional layer d. Ignoring basic neural network structures 19. What is the primary purpose of the error backpropagation algorithm in training neural networks? a. To adjust the weights of the network based on prediction errors b. To introduce randomness in neural network training c. Ignoring the training process d. To increase computational complexity 20. What is the primary purpose of an activation function in a neural network? a. To initialize weights b. To introduce non -linearity c. To store training data d. To connect neurons 21. What is the name of the method described below? __ is the process of predicting the category of given data points. Categories are sometimes called as targets or labels. a. Classification b. Clustering c. Dimensionality Reduction d. Feature Extraction 22. Which of the following open-source licenses al allows commercial ial use of the software? a. MIT b. GPL c. Apache d. All of the above
- 7. How can lor and Al enhance precision farming in agriculture? a. By avoiding real-time data collection b. By providing insights into soll health and crop conditions c. Excluding machine learning algorithms d. Ignoring weather forecasts a. Why is protecting user privacy particularly crucial in Al applications such as facial recognition? a. To encourage indiscriminate data sharing b. To prevent misuse and surveillance without consent c. To prioritize public accessibility of facial data d. To avoid accuracy in facial recognition models 9. Which of the following are subdomains of Al? a. Machine learning b. Deep learning c. Neural networks d. All the above 10. How does ensemble learning differ from using a single model? a. Ensemble learning relies solely on one model for predictions. b. Ensemble learning avoids combining multiple models. c. Ensemble learning combines predictions from multiple models to make a final predictic 1. d. Ensemble learning prioritizes model simplicity over accuracy. 11. What is Scikit-learn primarily used for? a. Data visualization b. Machine learning model creation c. Real-time data streaming d. Image processing 12. What does PMBOK stand for in the context of project management? a. Project Management Body of Knowledge b. Personal Management Basics of Knowledge c. Project Management Book of Knowledge d. Professional Management and Business Operations Knowledge 3. Which of the following is not a deep learning framework? 2. TensorFlow . Keras . PyTorch NumPy How does "Hard Voting"differ from "Soft Voting"in a Voting Classifier? Hard Voting considers only one model's prediction, while Soft Voting considers predictions from all els. Hard Voting makes a decision based on a majority vote, while Soft Voting considers the confidence of model. oth Hard Voting and Soft Voting involve the same decision-making process. oft Voting relies on a single model, while Hard Voting considers predictions from all models. Page 2 of 4