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Build a Machine Learning Workflow with Keras TensorFlow 2.0
This course focuses on Keras as part of the TensorFlow 2.0 ecosystem, including sequential APIs to build relatively straightforward models of stacked layers, functional APIs for more complex models, and model subclassing and custom layers.
Implementing and Operating AWS Machine Learning Solutions
Training a machine learning model is only the first step. This course will teach you how to deploy, monitor, and scale your machine learning solution in preparation for the Machine Learning Specialty exam.
Fundamentals of Machine Learning on AWS
Machine learning is one of the hottest fields in the world today. This course will teach you how to get started solving business problems with AWS machine learning technologies.
Building Features for Computer Vision in Microsoft Azure
This course will cover how to leverage both an algorithmic as well as a deep learning approach for building features from image data on Microsoft Azure.
Demystifying the AWS Certified Machine Learning Specialty Exam
The AWS Machine Learning Specialty Exam covers four distinct domains. This course will review the exam, the concepts from these four domains, and techniques for how you can best prepare for it.
Getting Started with Tensorflow 2.0
This course focuses on introducing the TensorFlow 2.0 framework - exploring the features and functionality that it offers for building and training neural networks. This course discusses how TensorFlow 2.0 differs from TensorFlow 1.x and how the use of the Keras high-level API and eager execution makes TensorFlow 2.0 a very easy to work with even for complex models.
Creating & Deploying Microsoft Azure Machine Learning Studio Solutions
This course will provide an introduction to the power, flexibility and scalability of Azure Machine Learning. You will learn to implement the data science process, to prepare data and integrate data sources for use in machine learning experiments.
Designing a Machine Learning Model
This course covers the important differences between various canonical problems in machine learning, as well as the considerations in choosing the right solution techniques, based on the specifics of the problem you are trying to solve and the data that you have available.
Designing Machine Learning Solutions on Microsoft Azure
This course will cover how to leverage Azure Machine Learning for a successful data science initiative across the key components of workflow, data pipeline, and infrastructure.
Introduction to TensorFlow
This course is focused on using the flexibility and “ease of use” of TensorFlow 2.x and Keras to build, train, and deploy machine learning models. You will learn about the TensorFlow 2.x API hierarchy and will get to know the main components of TensorFlow through hands-on exercises. We will introduce you to working with datasets and feature columns. You will learn how to design and build a TensorFlow 2.x input data pipeline. You will get hands-on practice loading csv data, numPy arrays, text data, and images using tf.Data.Dataset. You will also get hands-on practice creating numeric, categorical, bucketized, and hashed feature columns. We will introduce you to the Keras Sequential API and the Keras Functional API to show you how to create deep learning models. We’ll talk about activation functions, loss, and optimization. Our Jupyter Notebooks hands-on labs offer you the opportunity to build basic linear regression, basic logistic regression, and advanced logistic regression machine learning models. You will learn how to train, deploy, and productionalize machine learning models at scale with Cloud AI Platform.
Deploying and Managing Models in Microsoft Azure
In this course, you'll learn about how data science practitioners can utilize tools for managing the models they create. You'll also see those tools showcased in Microsoft Azure.
AWS Foundations: Machine Learning Basics
In this course, you get an overview of the concepts, terminology, and processes of the exciting field of machine learning!
Developing Models in Microsoft Azure
It's common to spend a lot of resources on identifying an optimal machine learning model. In this course, you will learn how to simplify this process using various cutting edge features offered by Microsoft Azure Machine Learning service.
Building, Training, and Validating Models in Microsoft Azure
This course gives Microsoft Azure Data Scientists a road map on how to build, train, and validate machine learning models in Azure.
AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer
Join Joe Pringle, AWS for an inside perspective on how to understand machine learning and how to put it to work in your role.
Preparing Data for Machine Learning with Java
Data is at the heart of machine learning. This course will teach you how to bring data into Java from various sources, as well as how to perform basic tidying up and transformations in view of further processing by specialized Java ML libraries.
Demystifying Machine Learning Operations (MLOps)
Managing the machine learning process using recommended practices is a must to enable collaboration, tracing, and real-time monitoring. This course will teach you what are the main concerns and issues you need to consider while developing a machine learning model and after deploying it.
Implementing Machine Learning Workflow with RapidMiner
In this course, you will learn how you can develop your machine learning workflow using RapidMiner Studio, a data science platform for data preparation, machine learning, and predictive model deployment.
Implementing Machine Learning Workflow with Weka
In this course, you will learn how you can develop your machine learning workflow using Weka, an open-source machine learning software for data preparation, machine learning, and predictive model deployment.
Implement Image Recognition with a Convolutional Neural Network
Image recognition is used in a wide variety of ways in our daily lives. This course will teach you how to tune and implement convolutional neural networks in order to implement image recognition and classification on a business case.
Build a Rating Recommendation Engine with Collaborative Filtering
Recommendation systems pervade a great number of aspects of our daily lives. This course will teach you how to build your very own recommendation system using a technique called collaborative filtering.
Deep Learning Application for Marketing
This course will teach you how Deep learning is integrated into the daily practices of digital marketing, in order to improve digital marketing practices in the data driven era, and maintain better connections with existing and potential users.
Building Machine Learning Solutions with TensorFlow.js 2
In this course, you'll learn to use TensorFlow.js to build, train, and deploy machine learning and deep learning models to power client-side and server-side applications using the JavaScript language.
Build, Train, and Deploy Your First Neural Network with TensorFlow 2
In this course, you will learn the basic principles of machine learning and neural networks so you can quickly create, train, and deploy a neural network with TensorFlow.
Key Features of Pluralsight
- Skill Assessments Pluralsight's Skill IQ and Role IQ features allow learners to assess their current skills and determine which areas require improvement. These personalized assessments provide insights into where users stand compared to industry standards, guiding them toward the most suitable courses.
- Learning Paths The platform offers well-structured learning paths that guide learners through a series of courses designed to develop specific skills. Whether you're aiming for certification or mastering a new programming language, Pluralsight’s learning paths ensure that you systematically achieve your learning objectives.
- On-Demand Courses Pluralsight’s courses are available on demand, which gives learners the flexibility to study at their own pace. This allows working professionals to balance their learning with their job responsibilities.
- Enterprise Solutions In addition to individual learning, Pluralsight provides enterprise solutions that help organizations manage and track the learning progress of their teams. Companies can benefit from tailored learning paths, assessments, and analytics to ensure that their workforce stays competitive.
- Offline Viewing Learners can download courses and view them offline using Pluralsight's mobile app, making it convenient for users to continue learning even without an internet connection.
- Certification Preparation Pluralsight offers courses that prepare learners for a wide range of professional certifications in areas such as AWS, Microsoft, Google Cloud, and CompTIA. These courses help professionals gain the credentials they need to advance in their careers.
- Interactive Learning Pluralsight's hands-on learning experience allows users to practice what they learn in real-world scenarios. The platform offers interactive labs and projects where learners can apply their skills in simulated environments.
Pluralsight Pricing and Plans
Pluralsight offers a variety of pricing plans to accommodate both individual learners and enterprises.- Individual Plans: Starting with a free trial, individuals can subscribe to the monthly or annual plan. The annual subscription provides significant savings and access to the entire course library.
- Team Plans: For businesses, Pluralsight offers team and enterprise-level solutions with advanced analytics, reporting features, and role-based learning pathways. These plans ensure that teams can collaborate and learn efficiently while tracking their progress through in-depth analytics.
Why Choose Pluralsight?
- Expert-Led Content All courses on Pluralsight are created by industry experts who bring real-world experience and knowledge to the table. This ensures that learners get the most up-to-date and relevant information.
- Constantly Updated Courses Pluralsight continuously updates its course content to reflect the latest industry trends, ensuring that learners always have access to the most current skills and knowledge.
- Diverse Range of Topics From cybersecurity and IT operations to creative topics like video production and design, Pluralsight offers courses across a diverse range of subjects, making it a one-stop solution for tech professionals and creatives alike.
- Personalized Learning Pluralsight provides a personalized learning experience with its skill assessments and role-specific learning paths. This feature ensures that learners only focus on areas they need to improve, saving time and effort.
Popular Courses Offered by Pluralsight
Some of the most popular courses on Pluralsight include:- JavaScript: Getting Started Ideal for beginners, this course provides a comprehensive introduction to one of the most widely used programming languages in web development.
- AWS Certified Solutions Architect - Associate This course prepares learners for the AWS certification exam and equips them with the skills needed to design robust cloud architectures.
- Python Fundamentals Perfect for learners new to Python, this course covers the basics of programming in one of the most versatile programming languages.
- CISSP Certification Prep Aimed at cybersecurity professionals, this course prepares learners for the CISSP certification, covering critical areas of information security.