Understanding deep learning and Keras

- [Instructor] Why is Deep Learning so popular? Well, there are four simple reasons to it. Number one reason is data growth. Unprecedented volumes of data enable training of more sophisticated models. Number two is hardware advancements. Powerful GPUs accelerate training, making deep learning more feasible. And number three is Python and open-source libraries enhance accessibility and collaboration. And lastly, cloud computing allows for scalable, resource, independent model deployment. Is this an Australian Labradoodle? We may need the following to know the answer. Nose experts, eye experts, ear experts, and coat experts. Let's train high school students to detect this. Teacher Anne is asking students, is this an Australian Labradoodle? Give me an answer between zero and one, where one is yes and zero is no. We will assign different tasks to each student. For example, student Yogita is our nose expert, and Mike is our eye expert. Rohit is our ear expert, and Hazel is our coat expert. Each student focused on this particular area when they see a dog photo, and give their best guess from zero to one. Then let's take each student's score and multiply it with the weight here. The weight means how much importance each part of the dog carries while deciding whether or not it is an Australian Labradoodle. While in this particular example, the answer is .55, so very close to either way. Then let's take each student's score and multiply it with the weight here. The weight means how much importance each part of the dog carries while deciding whether or not it's an Australian Labradoodle. The answer is .55. So very close either way. Now, let's say we are taking this up a notch and now have more people who can help us. We then divide the dog photo into face and body and have the students report their answer to each teacher, Anne and Heather. In this case, Yogita and Mike are reporting their values to Anne, which makes up the face value. Then Rohit and Hazel are reporting their values to the teacher Heather, which makes the body value. We then calculate the total estimate using the weights of the face and body to give our final answer whether this image is an Australian Labradoodle or not. And we give this answer to the principle then. Weight tells us about which feature is more important while calculating the total value we give to Dan. What we did is nothing but a neural network. The very important part of deep learning. In this case, students are the individual neurons, input layer, and the teachers are the hidden layer, and the principle is the output layer. But these were just guesses. How do we train the students to come up with good guesses for the next time? Well, let's get help from our veterinarian, Rohit. After we collect the answers from students and do the calculations for the total number. School principal then takes this to the vet, Rohit, who knows the correct answer. Based on this correction, Dan provides feedback to the teachers, and teachers provide feedback to the students to do better next time. Let's put these members back to the building. Thanks for demoing guys, we appreciate you. By the way, the demo crew belongs to the Keras High. We can use this metaphor to explain that Keras is nothing but a deep learning tool used as a repper utilizing more code intensive tools like TensorFlow and Theano. There are others, but in this course, these are what we will focus on. Keras is not just a tool, it's your gateway to building neural networks that rival those at tech titans, like Google and Facebook. With Keras, complexity doesn't stand a chance. It's crafted to streamline your journey into deep learning. It lets you construct advanced neural networks with just a handful of code lines, but don't be fooled by its simplicity. Keras is a powerhouse operating at top titans like TensorFlow and Theano, offering you their strengths with none of the hassle, which enables a lot of real-word applications with just a few lines of code. And there is more. Keras is not just about building from scratch. It's about standing on the shoulders of giants. With its prebuilt models and best practice parameters, Keras equips you with tried and tested defaults that propel you towards your goal. It's like having a trusted mentor by your side, guiding you step by step. Whether you are looking to recognize the wonders of the world with pre-trained models, or dreaming of crafting a custom vision with your unique data sets, Keras is your companion. Your enabler. Join me as we embark on this transformative journey to harness the true potential of deep learning with Keras. Let's build, innovate, and transcend the ordinary, one neural layer at a time.