About us
Aim
TensorScience aims to link the science of machine learning and artificial intelligence on the one hand (of which certain areas are still highly theoretical and out of the realms of current computing capacities) to what is currently possible computationally on the other hand. The tutorials draw upon a combination of code developed internally, open source software, and chunks of code on machine learning that are available in repositories such as GitHub and Stack Overflow, making these more accessible to the public.
Our goal
We dive deeply into the world of machine learning with Python. Our mission is to provide a comprehensive repository of guides, tutorials, and resources that empower both beginners and seasoned practitioners to harness the transformative power of machine learning across a variety of complex domains.
The aim is to be an open-source and free repository of guides and tutorials that use deep learning to solve complex challenges, such as those involving object recognition, optical character recognition and natural language processing. It aims to link the science of machine learning on the one hand - which in certain areas is still theoretical and out of the realms of current computer capabilities - and software and chunks of code on machine learning on the one hand that are available on the internet.
At TensorScience, we believe in the democratization of technology and knowledge. That’s why we’ve committed to keeping our platform free and open source, ensuring that anyone with an interest in machine learning can access high-quality educational content without barriers.
Areas
Our extensive collection of materials covers a wide array of topics within the machine learning spectrum, including but not limited to:
Object Recognition: Learn how to enable machines to identify and classify objects within images or videos, a crucial skill for applications ranging from autonomous vehicles to security systems.
Optical Character Recognition (OCR): Discover methods for converting different types of images of typed, handwritten, or printed text into machine-encoded text, facilitating tasks such as document digitization and automated data entry.
Natural Language Processing (NLP): Delve into the realm of NLP to teach machines how to understand, interpret, and generate human language, opening doors to innovations like chatbots, translation services, and sentiment analysis.
And More: Explore a variety of other machine learning challenges and solutions, ensuring you’re equipped with the knowledge to tackle the most cutting-edge problems in the field.
Our guides are meticulously crafted by experts and enthusiasts in the field, ensuring that you receive accurate, up-to-date, and practical information. Each tutorial is designed to be hands-on, with code examples and detailed explanations that enable you to learn by doing.
Whether you’re a student looking to augment your studies, a professional seeking to upskill, or a hobbyist passionate about machine learning, TensorScience.com is your ally on this journey. We’re constantly updating and expanding our content to keep pace with the rapidly evolving landscape of machine learning, so you can stay at the forefront of technological innovation.
If you have questions, suggestions, or other inquiries, please contact us through our Contact page.
Our vision
The knowledge on machine learning and its capabilities has existed for decades but has only become graspable in the past decade with innovations in computer hardware (e.g. gradient processing capabilities in GPUs) and software. This is a very exciting development. Humans have for the most part just crawled out of the slime. In the last four hundred years, human cognition has delved into realms previously inaccessible by any other creature in the last billion; complex and abstract mathematics, chemistry, physics, and recently, computer intelligence has transformed our world.
Our recent ancestors didn’t know how a television worked, and only rode on an airplane a few times in their lifes. Today, children are walking up to televisions and swiping right in frustration. Our very brains are changing due to the heightened pace afforded by technological advances.
In the matter of a few decades, humans will cease to exist in the way we have for the past 4 million years. The advent of server side architectures transacting everything from commerce to entertainment shapes our lives, changes our environment, and recommends what we should do next. Human machine interfaces are becoming ubiquitous and will, hopefully, be important drivers of human progress in the years to come.
The thin veil that makes all this possible is the internet, and the machine intelligence that shapes it. So far, this intelligence is embryonic; business rules are not bonafide intelligence, and as such, most applications today are governed by static inputs and outputs. A google result is very useful for retrieving information, yet it fares very poorly in actually answering your question.
So what then is intelligence?
Using a broad brush, the following might be considered an al fresco mural defining intelligence,
- the capacity to acquire and extract knowledge from observations,
- the ability to respond and apply knowledge given observations,
- the capacity to understand and foresee the intention of other systems
- the ability to recognize and draw (plausible) inferences from observations
- and most importantly, posing questions and trying to answer them
Machines are getting closer and closer to being able to do this. We hope that the guides on this website will help you in learning from, and applying, such artificial intelligence.
Join our community at TensorScience.com and start mastering machine learning with Python today. Together, we can unlock the potential of artificial intelligence to solve some of the most complex challenges of our time. Thank you for choosing TensorScience as your guide through the exciting world of machine learning. Let’s learn, build, and innovate together.
The TensorScience Team