Coding TensorFlow

Course Overview

What does this course tell?
(Please note that the following overview content is from Alison)
Recommendation systems overview (Building recommendation systems with TensorFlow)Content-based filtering & collaborative filtering ( building recommendation systems Natural Language Processing - Tokenization (NLP Zero to Hero - Part 1)Sequencing - Turning sentences into data (N LP Zero toHero - Part 2)Training a model to recognize sentiment in textML with Recurrent Neural Networks (NLI Zero tohero - Part 4)Long Short-Term Memory for NLP (Nli Zero to hero - Part 5)Training an AI to create poetry (Nlli Zero to HERO - Part 6)Neural Structured Learning - Part 3: Training with synthesized graphs Adversarial learning

We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
In this course, students will acquire skills and knowledge in coding TensorFlow, building recommendation systems, natural language processing, tokenization, sequencing, training a model to recognize sentiment in text, machine learning with recurrent neural networks, long short-term memory for NLP, training an AI to create poetry, neural structured learning, and training with synthesized graphs and adversarial learning.
lHow does this course contribute to professional growth?
This course contributes to professional growth by providing a comprehensive overview of recommendation systems and how to build them using TensorFlow. It covers content-based filtering and collaborative filtering, natural language processing, tokenization, sequencing, training a model to recognize sentiment in text, machine learning with recurrent neural networks, long short-term memory for NLP, training an AI to create poetry, and neural structured learning. By taking this course, professionals can gain a better understanding of the fundamentals of recommendation systems and how to use TensorFlow to build them. This knowledge can be applied to a variety of industries, from e-commerce to healthcare, and can help professionals stay ahead of the curve in their respective fields.

Is this course suitable for preparing further education?
Yes, this course is suitable for preparing further education. It covers a range of topics related to recommendation systems, natural language processing, machine learning, and neural structured learning. It also provides hands-on experience with TensorFlow, a popular open-source library for deep learning.