In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

Grow your machine learning skills with scikit-learn in Python. Use real-world datasets in this interactive course and learn how to make powerful predictions!

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

You learn to develop scripts that use image recognition to interact with elements by using the IBM RPA Recorder.

In this talk, Anne Currie will discuss tech ethics in the middle of an event.

This course will teach you how to build, train and evaluate neural network models for classification and regression tasks using TensorFlow 2.X.

As part of the TensorFlow Developer certification, this course focuses on computer vision. By the end of the course, you will know everything to build computer vision neural networks that can handle complex real-world images using TensorFlow.

This course will teach you all the NLP techniques in Tensorflow 2 needed to do amazing things like generate text or classify intention.

In this course, TensorFlow Developer Certificate - TensorFlow Developer Skills , you will learn several items. First, you will learn how to compile and run Python programs in PyCharm. Next, you will discover how to find information about TensorFlow APIs. Then, how to solve error messages fro m the TensorFlow API. Finally, how to save ML models and check the model file size

TensorFlow is a powerful open-source library for machine learning and numerical computation to develop and train deep learning models. This course will teach you how to analyze time series data and accurately forecast future events.

This Getting Started With Tensorflow tutorial will help you in understanding how to use and reuse Tensorflow effectively.

Learn the bag of words technique for text mining with R.