Add FAQs to Docs Datasets and Help sections (#14211)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

docs/en/help/FAQ.md

@@ -8,7 +8,9 @@ keywords: Ultralytics, YOLO, FAQ, object detection, hardware requirements, fine-
 
 This FAQ section addresses some common questions and issues users might encounter while working with [Ultralytics](https://ultralytics.com) YOLO repositories.
 
-## 1. What is Ultralytics and what does it offer?
+## FAQ
+
+### 1. What is Ultralytics and what does it offer?
 
 Ultralytics is a computer vision AI company that develops and maintains state-of-the-art object detection and image segmentation models, primarily focusing on the YOLO (You Only Look Once) family of models. Ultralytics offers:
 
@@ -18,7 +20,7 @@ Ultralytics is a computer vision AI company that develops and maintains state-of
 - [Tools for training, testing, and deploying models](https://docs.ultralytics.com/modes/)
 - [Extensive documentation and community support](https://docs.ultralytics.com/)
 
-## 2. How do I install the Ultralytics package?
+### 2. How do I install the Ultralytics package?
 
 To install the Ultralytics package, you can use pip, the Python package manager. Open a terminal or command prompt and run:
 
@@ -34,7 +36,7 @@ pip install git+https://github.com/ultralytics/ultralytics.git
 
 For more details, refer to the [quickstart guide](https://docs.ultralytics.com/quickstart/).
 
-## 3. What are the system requirements for running Ultralytics models?
+### 3. What are the system requirements for running Ultralytics models?
 
 Minimum requirements:
 
@@ -52,7 +54,7 @@ Recommended:
 
 For more information, visit [YOLO Common Issues](https://docs.ultralytics.com/guides/yolo-common-issues/).
 
-## 4. How can I train a custom YOLOv8 model on my own dataset?
+### 4. How can I train a custom YOLOv8 model on my own dataset?
 
 To train a custom YOLOv8 model:
 
@@ -73,7 +75,7 @@ results = model.train(data="path/to/your/data.yaml", epochs=100, imgsz=640)
 
 For detailed instructions, refer to the [training guide](https://docs.ultralytics.com/modes/train/).
 
-## 5. What pretrained models are available in Ultralytics?
+### 5. What pretrained models are available in Ultralytics?
 
 Ultralytics offers a range of pretrained YOLOv8 models for various tasks:
 
@@ -83,7 +85,7 @@ Ultralytics offers a range of pretrained YOLOv8 models for various tasks:
 
 These models vary in size and complexity, offering different trade-offs between speed and accuracy. Learn more about [pretrained models](https://docs.ultralytics.com/models/yolov8/).
 
-## 6. How do I perform inference using a trained Ultralytics model?
+### 6. How do I perform inference using a trained Ultralytics model?
 
 To perform inference with a trained model:
 
@@ -105,7 +107,7 @@ for r in results:
 
 For more details, visit the [prediction guide](https://docs.ultralytics.com/modes/predict/).
 
-## 7. Can Ultralytics models be deployed on edge devices or in production environments?
+### 7. Can Ultralytics models be deployed on edge devices or in production environments?
 
 Yes, Ultralytics models can be deployed on various platforms:
 
@@ -116,7 +118,7 @@ Yes, Ultralytics models can be deployed on various platforms:
 
 Ultralytics provides export functions to convert models to various formats for deployment. Learn more about [deployment options](https://docs.ultralytics.com/guides/model-deployment-options/).
 
-## 8. What's the difference between YOLOv5 and YOLOv8?
+### 8. What's the difference between YOLOv5 and YOLOv8?
 
 Key differences include:
 
@@ -128,7 +130,7 @@ Key differences include:
 
 For a detailed comparison, visit [YOLOv5 vs YOLOv8](https://www.ultralytics.com/yolo).
 
-## 9. How can I contribute to the Ultralytics open-source project?
+### 9. How can I contribute to the Ultralytics open-source project?
 
 To contribute:
 
@@ -140,7 +142,79 @@ To contribute:
 
 You can also contribute by reporting bugs, suggesting features, or improving documentation. Refer to the [contributing guide](https://docs.ultralytics.com/help/contributing/).
 
-## 10. Where can I find examples and tutorials for using Ultralytics?
+### 10. How do I install the Ultralytics package in Python?
+
+To install the Ultralytics package in Python, you can use pip by running the following command in your terminal or command prompt:
+
+```bash
+pip install ultralytics
+```
+
+If you want the latest development version, you can install it directly from the GitHub repository:
+
+```bash
+pip install git+https://github.com/ultralytics/ultralytics.git
+```
+
+For additional instructions and details, you can refer to the [quickstart guide](https://docs.ultralytics.com/quickstart/).
+
+### 11. What are the main features of Ultralytics YOLO?
+
+Ultralytics YOLO offers several advanced features to enhance object detection and image segmentation tasks:
+
+- **Real-Time Detection:** Efficient detection and classification of objects in real-time.
+- **Pre-Trained Models:** Access to a variety of pretrained models that balance speed and accuracy ([Pretrained Models](https://docs.ultralytics.com/models/yolov8/)).
+- **Custom Training:** Easily fine-tune models on custom datasets ([Training Guide](https://docs.ultralytics.com/modes/train/)).
+- **Wide Deployment Options:** Models can be exported to various formats like TensorRT, ONNX, and CoreML for deployment on different platforms ([Deployment Options](https://docs.ultralytics.com/guides/model-deployment-options/)).
+- **Extensive Documentation:** Comprehensive documentation and community support to help users at all levels ([Documentation](https://docs.ultralytics.com/)).
+
+For further information, you can explore the [YOLO models page](https://docs.ultralytics.com/models/yolov8/).
+
+### 12. How can I improve the performance of my YOLO model?
+
+Improving the performance of your YOLO model can be achieved through several techniques:
+
+1. **Hyperparameter Tuning:** Experiment with different hyperparameters to optimize model performance ([Hyperparameter Tuning Guide](https://docs.ultralytics.com/guides/hyperparameter-tuning/)).
+2. **Data Augmentation:** Use techniques like flip, scale, rotate, and color adjustments to enhance your training dataset.
+3. **Transfer Learning:** Start with a pre-trained model and fine-tune it on your specific dataset ([Train YOLOv8](https://docs.ultralytics.com/modes/train/)).
+4. **Export to Efficient Formats:** Export your model to optimized formats like TensorRT or ONNX for faster inference ([Export](../modes/export.md)).
+5. **Benchmarking:** Use the benchmarking tools available to measure and improve the inference speed and accuracy ([Benchmark Mode](https://docs.ultralytics.com/modes/benchmark/)).
+
+### 13. Can I deploy Ultralytics YOLO models on mobile and edge devices?
+
+Yes, you can deploy Ultralytics YOLO models on mobile and edge devices by converting them to supported formats. Here are some options:
+
+- **Mobile:** Convert models to TFLite or CoreML for integration into Android or iOS apps ([TFLite Integration Guide](https://docs.ultralytics.com/integrations/tflite/) and [CoreML Integration Guide](https://docs.ultralytics.com/integrations/coreml/)).
+- **Edge Devices:** Use TensorRT or ONNX for optimized inference on devices like NVIDIA Jetson or other edge hardware ([Edge TPU Integration Guide](https://docs.ultralytics.com/integrations/edge-tpu/)).
+
+For detailed instructions on different deployment options, visit the [deployment options guide](https://docs.ultralytics.com/guides/model-deployment-options/).
+
+### 14. How can I perform inference using a trained Ultralytics YOLO model?
+
+To perform inference using a trained Ultralytics YOLO model, follow these steps:
+
+1. **Load the Model:**
+
+    ```python
+    from ultralytics import YOLO
+
+    model = YOLO("path/to/your/model.pt")
+    ```
+
+2. **Run Inference:**
+
+    ```python
+    results = model("path/to/image.jpg")
+
+    for r in results:
+        print(r.boxes)  # print bounding box predictions
+        print(r.masks)  # print mask predictions
+        print(r.probs)  # print class probabilities
+    ```
+
+For more detailed instructions, check out the [prediction guide](https://docs.ultralytics.com/modes/predict/).
+
+### 15. Where can I find examples and tutorials for using Ultralytics?
 
 You can find examples and tutorials in several places: