Welcome to your journey into the fascinating world of deep learning! This blog post will guide you through a two-day workshop designed to introduce you to the essential concepts of building deep learning models using TensorFlow and Keras via R. Whether you’re a newcomer or have some experience under your belt, this workshop is tailored to provide you with the skills needed to apply deep learning in real-world scenarios.

Overview of the Workshop

This intensive workshop covers:

• Understanding the architectures that drive deep learning
• Applying various deep learning algorithms, including MLPs, CNNs, RNNs, and LSTMs
• Tuning hyperparameters to optimize model performance
• Interpreting model results effectively
• Hands-on applications like computer vision, natural language processing, and collaborative filtering

By the end of the workshop, you will possess a solid grasp of deep learning and be equipped with a systematic approach for producing high-quality modeling results.

Is This Course for You?

Before signing up, ask yourself these questions:

• Are you relatively new to deep learning but excited to learn?
• Do you have experience with R, particularly the tidyverse, functions, and control and iteration statements?
• Are you familiar with machine learning processes like data splitting and hyperparameter tuning?

If you answered “yes” to all three, this workshop is a perfect fit for you!

Prework Requirements

To get the most out of this workshop, you’ll need to have a good foundation in the following:

• Familiarity with the Tidyverse and control flow
• Understanding of basic machine learning concepts (HOML Ch. 1)
• Knowledge of the machine learning modeling process (HOML Ch. 2)
• Experience with feature engineering (HOML Ch. 3)

These resources will lay a solid groundwork, allowing you to dive deeper into the intricacies of deep learning during the workshop.

Workshop Schedule

The workshop is mainly notebook-focused, meaning most of the time will be spent in R notebooks. Here’s a glimpse of what to expect:

Day 1

• 09:00 – 09:30: Introduction Slides
• 09:30 – 10:30: Deep learning ingredients Notebook
• 11:00 – 12:30: Deep learning recipe & mini-project on predicting home sales prices Notebook
• 13:30 – 15:00: Exploring Computer Vision with CNNs Notebook
• 15:30 – 17:00: Project on classifying natural images Notebook

Day 2

• 09:00 – 10:30: Word embeddings and IMDB Notebook
• 11:00 – 12:30: Collaborative filtering Notebook
• 13:30 – 15:00: RNNs and LSTMs Notebook
• 15:30 – 17:00: Wrap up and project on detecting duplicate Quora questions Notebook

Troubleshooting & Tips

As with any technical workshop, you might face a few hiccups along the way. Here are some troubleshooting tips:

• Make sure all necessary packages are pre-installed. If not, refer to the pre-installation instructions.
• If you encounter issues with RStudio Cloud set-up, follow the server setup instructions.
• For additional insights and other development projects, stay connected with fxis.ai.

By preparing well, you can maximize your learning experience and tackle challenges head-on!

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

Conclusion

Embarking on this workshop will surely empower you with a practical understanding of deep learning models in R. Relate the deep learning components to ingredients in a recipe; just as each ingredient has a unique role, every model architecture contributes differently toward the end goal. Harness the power of deep learning and explore its applications across various domains!