Udemy Online Course - Deep learning Calculus - Data Science - Machine Learning AI Mastering Calculus for Deep learning / Machine learning / Data Science / Data Analysis / AI using Python You start by learning the definition of function and move your way up for fitting the data to the function which is the core for any Machine learning, Deep Learning, Artificial intelligence, Data Science Application. Once you have mastered the concepts of this course, you will never be blind while applying the algorithm to your data, instead you have the intuition as how each code is working in background. What you'll learn Build Mathematical intuition especially Calculus required for Deep learning, Data Science and Machine Learning The Calculus intuition required to become a Data Scientist / Machine Learning / Deep learning Practitioner How to take their Data Science / Machine Learning / Deep learning career to the next level Hacks, tips & tricks for their Data Science / Machine Learning / Deep learning career Implement Machine Learning / Deep learning Algorithms better Learn core concept to Implement in Machine Learning / Deep learning Who this course is for: Data Scientists who wish to improve their career in Data Science. Deep learning / Machine learning practitioner who wants to take the career to next level Any one who wants to understand the underpinnings of Maths in Data Science, Machine Learning, Deep Learning and Artificial intelligence Any Data Science / Machine Learning / Deep learning enthusiast Any student or professional who wants to start or transition to a career in Data Science / Machine Learning / Deep learning Students who want to refresh and learn important maths concepts required for Machine Learning, Deep Learning & Data Science. Data Scientists who wish to improve their career in Data Science.
Understanding deep learning technology Understand correlation between deep learning, machine learning and artificial intelligence History of deep learning Deep learning networks A Powerful Skill at Your Fingertips Learning the fundamentals of deep learning puts a powerful and very useful tool at your fingertips. Jobs in deep learning area are plentiful, and being able to learn deep learning will give you a strong edge. Deep learning is becoming very popular. Tesla self-driving cars, Alexa, Siri, IBM Deep Blue and Watson are some famous example of deep learning application. Understanding deep learning is vital in information retrieval, image classification and autonomous car driving.
When we talk about data science or artificial intelligence, the two very common terminologies that come into account are MACHINE LEARNING and DEEP LEARNING. But it is substantially seen that both the terms are faultily used interchangeably. So let us find out what is the difference between the two and how both the terms are interrelated with each other.
The science of Machine Learning (ML) has been around since the 1970s, but low horsepower processors and limited data forced the progress of Machine Learning to slow down in the 1980s. Ever since Big Data has enabled the use of unlimited "variety, volume, and velocity" business data, Machine Learning resurfaced as a powerful game changer in the world of software algorithms. Google's acquisition of UK-based Deep Mind resurrected the struggling field of Deep Learning (DL) and renewed the self-training possibilities of machines. In Deep Learning, smart algorithms can aid computers to learn from one layer of data and apply that learning to the next layer without programming intervention. While Machine Learning encompasses the entire field of learning algorithms, Deep Learning involves specific types of learning models where the human programmer is not required to train computers.