Machine Learning courses

As with any fundamentals course, Introduction to Natural Language Processing in R is designed to equip you with the necessary tools to begin your adventures in analyzing text. Natural language processing (NLP) is a constantly...

Many times in machine learning, the goal is to find patterns in data without trying to make predictions. This is called unsupervised learning. One common use case of unsupervised learning is grouping consumers based on...

4.25

C​alcualte safety stock using SARIMA predictions combined with manipulaitng lead times.

We’ve come to expect personalized experiences online—whether it’s Netflix recommending a show or an online retailer suggesting items you might also like to purchase. But how are these suggestions generated? In this course, you’ll learn...

Deep learning is the machine learning technique behind the most exciting capabilities in diverse areas like robotics, natural language processing, image recognition, and artificial intelligence, including the famous AlphaGo. In this course, you'll g...

Why Learn Linear Regression in R? This course is an introduction to the topic of linear regression and how to implement them using the R programming language. Linear regression models are used in machine learning,...

The need to pack a bilingual dictionary for your European holiday or keeping one on your desk to complete your foreign language homework is a thing of the past. You just hop on the internet...

Have you left a review to express how you feel about a product or a service? And do you have a habit of checking a product’s reviews online before you buy it? This kind of...

4.46

This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summ...

4.66

BigQuery is Google's fully managed, NoOps, low-cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can...

4.58

Build natural language processing systems using TensorFlowProcess text, including tokenization and representing sentences as vectorsApply RNNs, GRUs, and LSTMs in TensorFlowTrain LSTMs on existing text to create original poetry and more

3.33

In this course, we’ll learn about more advanced machine learning methods that are used to tackle problems in the supply chain. We’ll start with an overview of the different ML paradigms (regression/classification) and where the...

4.58

Frame a business use case as a machine learning problem. Gain a broad perspective of machine learning and where it can be usedConvert a candidate use case to be driven by machine learningRecognize biases that...

4.65

Identify the purpose and value of the key Big Data and Machine Learning products in Google Cloud. Use Cloud SQL and Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud. Employ BigQuery to...

4.86

This course introduces you to one of the main types of modeling families of supervised Machine Learning: Classification. You will learn how to train predictive models to classify categorical outcomes and how to use error...

4.2

This is the fifth course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow...

In this course, you'll learn natural language processing (NLP) basics, such as how to identify and separate words, how to extract topics in a text, and how to build your own fake news classifier. You'll...

3.75

In this Google Cloud Lab, you will learn how to create the core components of a simple vision-based system to analyze a tennis serve using the Video Intelligence API and a pretrained AutoML Vision Object...

It is estimated that over 70% of potentially usable business information is unstructured, often in the form of text data. Text mining provides a collection of techniques that allows us to derive actionable insights from...

4.43

Use the Keras Sequential and Functional APIs for simple and advanced model creation Design and build a TensorFlow 2. x input data pipelineUse the tf. data library to manipulate data and large datasetsTrain, deploy, and...