Is your company prepared to excel in the ever-evolving technological world? As new technologies emerge and old methods change, workforce need to stay informed and ahead of the curve. This digital transformation list is designed to help you do just that. The following courses will prepare you to utilize the digital resources around you to their fullest potential and implement organization-wide change.
Deep learning (DL) is used across a broad range of industries as the fundamental driver of AI. Being able to apply deep learning with Java will be a vital and valuable skill, not only within the tech world but also the wider global economy, which depends upon solving problems with higher accuracy and much more predictability than other AI techniques could provide.
This step-by-step, practical tutorial teaches you how to implement key concepts and adopts a hands-on approach to key algorithms to help you develop a greater understanding of deep learning. You will learn how to use the DL4J library and apply deep learning to a range of real-world use cases. This course will also help you solve challenging problems in image processing, speech recognition, and natural language modeling; it will make you rethink what you can do with Java, showing you how to use it for truly cutting-edge predictive insights.
By the end of this course, you'll be ready to tackle deep learning with Java. Whether you come from a data science background or are a Java developer, you will become part of the deep learning revolution!
The code bundle for this course is available at https://github.com/PacktPublishing/Deep-Learning-with-JavaCOURSE OBJECTIVES
Deep Learning has caused the revival of Artificial Intelligence. It has become the dominant method for speech recognition (Google Assistant), computer vision (search for ""my pictures"" on Google Photos), language translation, and even game-related Artificial Intelligence (think AlphaGo and DeepMind). If you'd like to learn how these systems work and maybe make your own, Deep Learning is for you!
In this course, you’ll gain a solid understanding of Deep Learning models and use Deep Learning techniques to solve business and other real-world problems to make predictions quickly and easily. You’ll learn various Deep Learning approaches such as CNN, RNN, and LSTM and implement them with TensorFlow 2.0. You’ll program a model to classify breast cancer, predict stock market prices, process text as part of Natural Language Processing (NLP), and more.
By the end of this course, you’ll have a complete understanding to use the power of TensorFlow 2.0 to train Deep Learning models of varying complexities, without any hassle.
All the code and supporting files for this course are available on GitHub at https://github.com/PacktPublishing/Implementing-Deep-Learning-Algorithms-with-TensorFlow-2.0
- Understand what Deep Learning and TensorFlow 2.0 are and what problems they have solved and can solve
- Study the various Deep Learning model architectures and work with them
- Apply neural network models, deep learning, NLP, and LSTM to several diverse data classification scenarios, including breast cancer classification
- Predicting stock market data for Google
- Classifying Reuters news topics, and classifying flower species
- Apply your newly-acquired skills to a wide array of practical and real-world scenarios
Python is developed under an OSI-approved open source license, making it freely usable and distributable, even for commercial use. Python is a general-purpose programming language. Created nearly 30 years ago, it is now one of the most popular languages out there to use. Its popularity is particularly important in the data science and machine learning fields. But it is also a language that is easy to learn, and that’s why it has become the language most taught in universities.
Python interpreters are available for the main operating systems as well (Linux, Mac OS, Windows, Android, iOS, BSD, etc.) so it’s very flexible in where it is used. Python has a simple syntax that makes it suitable for learning to program as a first language. The learning curve is smoother than other languages such as Java, which quickly requires learning about Object Oriented Programming or C/C++ that require understanding pointers. Still, it's possible to learn about OOP or functional programming in Python when the time comes.
This course will help you identify potential cyber threats, including malware, phishing and session hijacking, and take important steps to protect your company's valuable information. Cyber-crime syndicates, along with the prevalence of mobile and cloud-based computing trends, have increased the risk of security breaches for all organizations. In this course, you will learn how to control physical access to your company’s computers and develop best practices for preserving your information assets. You will also examine the ways in which humans pose risks to information security. By the end of this course, you will gain effective strategies for protecting passwords, working with contractors and using encryption to safely access data on mobile devices. This brief video course includes audio narration, exercises, a final quiz, and an ask-a-mentor email feature for a complete learning experience.
- Identify potential cyber security breaches and demonstrate appropriate caution
- Control physical access to computers and apply best security practices to protect information
- Develop methods for protecting sensitive data on mobile devices
This course is for Class 12th appearing students