Learning about deep learning methods and technologies has made a surge with new powerful models displaying capabilities we have never seen before. AI models built for the average user like ChatGPT and DALLE-2 have brought a mainstream spotlight on artificial intelligence. Understanding the inner workings of deep learning can be as confusing. While the math and the development of a functioning AI model are extensive, the general idea can be broken down into easier steps to learn how you can get started on your journey. Let's go over the basics of where to start to grasp the complex topic of artificial intelligence and deep learning.

Understand the fundamentals of linear algebra and calculus, critical mathematical subjects underlying all of machine learning and data science Manipulate tensors using all three of the most important Python tensor libraries: NumPy, TensorFlow, and PyTorch How to apply all of the essential vector and matrix operations for machine learning and data science Reduce the dimensionality of complex data to the most informative elements with eigenvectors, SVD, and PCA Solve for unknowns with both simple techniques (e.g., elimination) and advanced techniques (e.g., pseudoinversion) Appreciate how calculus works, from first principles, via interactive code demos in Python Intimately understand advanced differentiation rules like the chain rule Compute the partial derivatives of machine-learning cost functions by hand as well as with TensorFlow and PyTorch Grasp exactly what gradients are and appreciate why they are essential for enabling ML via gradient descent Use integral calculus to determine the area under any given curve Be able to more intimately grasp the details of cutting-edge machine learning papers Develop an understanding of what's going on beneath the hood of machine learning algorithms, including those used for deep learning Solve for unknowns with both simple techniques (e.g., elimination) and advanced techniques (e.g., pseudoinversion) Develop an understanding of what's going on beneath the hood of machine learning algorithms, including those used for deep learning All code demos will be in Python so experience with it or another object-oriented programming language would be helpful for following along with the hands-on examples. Familiarity with secondary school-level mathematics will make the class easier to follow along with. If you are comfortable dealing with quantitative information -- such as understanding charts and rearranging simple equations -- then you should be well-prepared to follow along with all of the mathematics. All code demos will be in Python so experience with it or another object-oriented programming language would be helpful for following along with the hands-on examples. Familiarity with secondary school-level mathematics will make the class easier to follow along with.

A Greater Foundation for Machine Learning Engineering: Linear Algebra and Calculus with TensorFlow Who is this presentation for?

We are very excited to organize Global Artificial Intelligence(AI) Virtual Conference is held on Oct 11th to Oct 15th 2021. As we get closer to the conference, we want to invite you to participate in Global Big Data Conference Webinar - Online Warm-Up on Oct 7th (1.00PM - 2.15PM) PST. We will features with speakers from our upcoming Global AI Virtual Conference each of which will present a 15 minute sessions. Welcome to webinar hosted by Global Big Data Conference! In the last decade many different types of neural networks have been developed.

AI-powered increases in safety, productivity, and efficiency are already improving our world, and the best is yet to come! As it becomes increasingly evident how impactful AI can be, demand for employees with AI skills increases--demand is in fact already skyrocketing. The AI Programming with Python Nanodegree program makes it easy to learn the in-demand skills employers are looking for. You'll learn foundational AI programming tools (Python, NumPy, PyTorch) and the essential math skills (linear algebra and calculus) that will enable you to start building your own AI applications in just three months. Whether you're seeking a full-time role in an AI-related field, want to start applying AI solutions in your current role, or simply want to start learning the defining technology of our time, this is the perfect place to get started.