There are a few steps you can take to get started with deep learning as a beginner:

Educate yourself: Read up on the basics of deep learning and familiarize yourself with the terminology and concepts. There are many online resources available, including tutorials, blogs, and courses.

Choose a framework: There are several popular deep learning frameworks, such as TensorFlow, PyTorch, and Keras, that provide pre-built models and libraries for creating and training deep learning models. Choose one that you feel comfortable with and start experimenting.

Gather and prepare data: Deep learning models require large amounts of data to learn from. You can use publicly available datasets or create your own by collecting and labeling data. Make sure to preprocess and clean your data to ensure that it is suitable for training.

Build and train models: Use your chosen framework to build and train deep learning models. Start with simple models and gradually increase the complexity as you gain more experience.

Evaluate and fine-tune: Measure the performance of your models and adjust the hyperparameters as needed to improve their accuracy.

It's also a good idea to join online communities and forums where you can ask questions and learn from others who are also interested in deep learning.

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