TensorFlow is an innovative tool designed with scalability in mind. Aimed at accelerating the process of model building, it offers an array of tutorials, examples, and ample resources to facilitate the creation of machine learning solutions. TensorFlow's robust architecture and flexibility have made it one of the go-to tools for data scientists, researchers, and developers.

Originally developed by Google Brain's team, TensorFlow has rapidly evolved into an end-to-end platform for implementing machine learning projects. As it's an open-source tool, it provides anywhere, anytime accessibility to its comprehensive library. The information available in this library ranges from dataflow graphs for building machine learning models to applications for newbies and developers.

Recognizing the importance of a stable learning ground to kickstart the process, TensorFlow presents numerous tutorials. These are articulated to deepen understanding and broaden knowledge bases. The tutorials are interactive, engaging, and designed for a varied range of proficiencies. Novices can easily get started with beginners' guides, while experts can dig deeper with the advanced content.

Additionally, TensorFlow provides numerous examples, meticulously laid out in an easy-to-understand format. These examples serve as a practical learning approach, as they mirror real-life scenarios where machine learning can be employed. Whether it is a simple linear regression or a complex deep learning model you want to implement, TensorFlow's examples would guide you at each step of the process.

One of TensorFlow's strengths lies in its rich diversity of resources. These resources are translated into various languages, making TensorFlow's depth accessible to a global audience. They range from articles and studies, which help to understand new concepts, to troubleshooting documents, which address common issues that may be encountered. Inclusive in its approach, TensorFlow ensures an enabling environment for all users.

Moreover, TensorFlow also offers multi-platform support, ranging from desktops to mobiles and the cloud. This allows developers to flexibly deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code.

The scalability feature of TensorFlow is truly unique. It gives the ability to start building models on a small scale and then extend them to run on large-scale systems. In simpler terms, one can train a model on a local machine and then effortlessly deploy it in the cloud or on mobile devices.

To sum up, TensorFlow is a powerful tool built to revolutionize machine learning with its rich, accessible resources. It is directed to ease the creation of machine learning models, thus fostering a conducive environment for developers, researchers, and learners going forward. It's not just a tool; it's an opportunity to learn, create, and transform your machine-learning journey. To join the revolution, all you need is an understanding of machine learning fundamentals and the passion to create engaging, innovative models.