AI Learning is a hot topic these days. AI has quickly become the most talked-about technology in the world. It’s also one of the fastest-growing industries, with an expected growth rate of 33% per year through 2025. AI has many different applications and tools, making navigating this new landscape challenging for beginners to learn AI.
Essential Tools to Keep Your Skills Sharp
- AI Class: AI Class is an online platform that provides a great AI Learning environment. The website has lessons and courses and access to free tools such as Tensorboard and Jupyter Notebooks.
- Google Cloud Platform: GCP offers cloud services for building AI applications with machine learning APIs like the Translate API or Speech API. You can also train models on GPUs in the cloud with Google Compute Engine (GCE) instances and use BigQuery to analyze your data without having to set up an infrastructure of your own.
- AIY Projects: AIY Projects by Google allows you to build intelligent machines that interact with the natural world using inexpensive components connected over I/O on a Raspberry Pi board. AIY Projects offers many AI learning resources, including AIY Voice Kit models for building your natural language voice recognition system.
- Deeplearning.ai: This is the course I mentioned earlier taught by Andrew Ng and his team at deeplearning.ai. The lessons are available on Coursera to anyone who wishes to subscribe. Still, you can also take the courses as part of a specialization program. You pay an additional fee to receive an official certificate upon completion.
- Tensorboard: A suite of visualization tools tailored towards understanding deep neural networks (DNNs). You can use it during both training and inference time to gain insights into how DNNs work, optimize their accuracy, etc.
- Pyleyarn: This is a library that was built to help researchers and students develop AI applications. It’s free, open-source, written in Python/Cython, and it comes with documentation containing examples on how to use the different APIs which are available.
- Torch AI Learning Wiki – AI Vision Library for Computer Vision Research & Development
- Keras(with Tensorflow): A high-level neural networks API developed by Google Brain Team. It can be run on top of either TensorFlow or Theano. Many people prefer using this because it has excellent documentation. There are plenty of tutorials online if you ever get stuck.
- Caffe Machine learning framework created by Berkeley AI Research (BAIR) community for image recognition and deep learning. It is developed in C++ but has recently been ported to Python by a group of independent developers…
- AI Learning: TensorFlow – Deeplearning.net
- AI Vision Library for Computer Vision Research & Development
- AI Wiki Search Engine powered by AI Learning: An artificial intelligence search engine that uses machine learning algorithms to find relevant information from across the web, including Wikipedia articles on just about any topic you can think of.
- Machine Learnings’ curated collection of data science/machine learning resources. They cover tools, tutorials, videos, etc., with short descriptions or annotated screenshots, so they are easy to skim through quickly.
We hope this information has been helpful to you.