English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 2h 40m | 461 MB
Predictive analytics is a booming topic and is an applied field that employs a variety of quantitative methods using data to make predictions. Every company has data and needs prediction capabilities so that it can prepare well for the future. TensorFlow is an open source library for dataflow programming across a range of tasks.
Before you jump into a “Alexa” or a “Google Lens” or a “Virtual assistant”, you need to learn the fundamentals. This course will allow you to think with a broader perspective and start with small chunks of code.
In this course, you’ll understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we’ll build predictive analytics solutions using cutting-edge algorithms and Tensorflow. You’ll work with models such as KNN, Random Forests, and neural networks using the Tensorflow library.
By the end of the course, you’ll be all set to build high-performance predictive analytics solutions using Python and Tensorflow.