Inhalt: There are many beginner Python tutorials, but to build useful applications, you need to move beyond the basics. This course helps you on the journey to writing intermediate-level Python code. Instructor Jonathan Fernandes presents eight things that you should know how to do in Python. Topics include the Python any() and all() methods, using enumerate() and zip() methods, min() and max(), and more. For each topic, Jonathan provides a hands-on approach and then gives you a challenge (with solutions) to practice. Note: This course was created by Jonathan Fernandes. We are pleased to host this training in our library. Umfang: 00:56:56
Inhalt: Want to get up and running with Apache Spark as soon as possible? If you're well versed in Python, the Spark Python API (PySpark) is your ticket to accessing the power of this hugely popular big data platform. This practical, hands-on course helps you get comfortable with PySpark, explaining what it has to offer and how it can enhance your data science work. To begin, instructor Jonathan Fernandes digs into the Spark ecosystem, detailing its advantages over other data science platforms, APIs, and tool sets. Next, he looks at the DataFrame API and how it's the platform's answer to many big data challenges. Finally, he goes over Resilient Distributed Datasets (RDDs), the building blocks of Spark. Umfang: 01:58:11.00
Inhalt: Apache Spark is widely considered to be the top platform for professionals needing to glean more comprehensive insights from their data. In this course, explore one of the most exciting aspects of this big data platform-its ability to do deep learning with images. Before he fully delves into deep learning on Spark using Python, instructor Jonathan Fernandes goes over the different ways to do deep learning in Spark, as well as key libraries currently available. He then shows how to set up your Spark deep learning environment, work with images in Spark using the Databricks deep learning library, use a pre-trained model and transfer learning, and deploy models as SQL functions. Umfang: 00:42:32.00
Inhalt: Take a deeper dive into machine learning with Amazon Web Services (AWS). In this practical course, instructor Jonathan Fernandes helps to familiarize you with common machine learning tasks, demonstrating how to approach each one using key techniques: binary classification, multiclass classification, and regression. Throughout the course, he walks through several examples, using Kaggle datasets for hands-on exploration. Plus, he reviews some essential machine learning concepts and helps to familiarize you with other AWS capabilities, including SageMaker and Deep Learning AMIs. Umfang: 01:25:50.00
Inhalt: In a field where reproducible results are essential, Docker is rapidly emerging as one of the top tools for bringing efficiency to the work that data science teams-particularly those working in machine learning (ML)-are doing. Creating and developing ML models is often messy. Seasoned data scientists know that different versions of the same software can produce different results. With Docker, you can include the right versions of each needed dependency and library, so no one ever has to do any configuration. After the Dockerfile is built, you'll have exactly what you need. In this course, Jonathan Fernandes helps data scientists get up and running with Docker, demonstrating how to build a Dockerized ML application that can easily be shared. Along the way, he shares common use cases for the tool. Upon wrapping up this course, you'll be prepared to leverage the power of containers in your other ML projects. Umfang: 00:46:36.00
Inhalt: Cloud Video Intelligence API allows developers to leverage the power of machine learning to work smarter, not harder. Instead of poring over your footage to find a particular shot, you can leverage pretrained machine learning models to quickly detect the objects you're looking for. Video Intelligence API also offers useful features such as the ability to moderate content and perform speech-to-text transcription. In this course, Jonathan Fernandes helps you get started with Video Intelligence API, demonstrating how to make calls to the API with Python and use machine learning models to glean insights from videos. Along the way, Jonathan provides hands-on exercises that enable you to apply the concepts you're learning. Umfang: 00:30:16.00
Inhalt: Google Cloud Vision API encapsulates powerful machine learning models in an easy-to-use REST API, allowing developers to leverage the power of machine learning without needing to train models of their own. Vision API gives you the power to annotate your images and text, detect objects and faces, automatically identify product logos and landmarks, and more. In this hands-on course, instructor Jonathan Fernandes helps you get up and running with this powerful product. Jonathan demonstrates how to make calls to the API with Python and leverage services that allow you to extract text from images, detect labels and facial expressions, and work effectively with batches of images. Umfang: 01:09:13.00
Inhalt: Artificial intelligence (AI) is taking the world by storm. Manufacturing, healthcare, and a host of other industries are steadily adopting this technology to streamline processes, enhance predictability, and generally keep ahead of the curve. In this course, discover what it takes to successfully introduce AI to your organization. Instructor Jonathan Fernandes steps through how to determine whether your organization is ready for AI, as well as how to develop and present a compelling business case for adopting the technology. Plus, he shares how to successfully implement AI-including how to do so using the scrum methodology-how to handle data collection and AI modeling, deploy, and finally monitor AI models once in production. Umfang: 00:53:25.00
Inhalt: AWS DeepLens is the world's first deep learning-enabled video camera for developers. In this hands-on course, instructor Jonathan Fernandes helps you get started with this exciting new tool. Jonathan kicks off the course by acquainting you with how DeepLens works, how to set it up, and how to troubleshoot common issues. Next, he guides you through a variety of projects available with DeepLens, including ones dealing with object recognition. To wrap up, Jonathan provides an overview of future projects you can consider. Umfang: 00:33:50.00
Inhalt: Deep learning is a fairly recent and hugely popular branch of artificial intelligence (AI) that finds patterns and insights in data, including images and video. Its layering and abstraction give deep learning models almost human-like abilities-including advanced image recognition. Using OpenCV-a widely adopted computer vision software-you can run previously trained deep learning models on inexpensive hardware and generate powerful insights from digital images and video. In this course, instructor Jonathan Fernandes introduces you to the world of deep learning via inference, using the OpenCV Deep Neural Networks (dnn) module. You can get an overview of deep learning concepts and architecture, and then discover how to view and load images and videos using OpenCV and Python. Jonathan also shows how to provide classification for both images and videos, use blobs (the equivalent of tensors in other frameworks), and leverage YOLOv3 for custom object detection. Umfang: 00:49:04.00
Inhalt: Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more. Umfang: 01:19:16.00
Inhalt: pandas is an open-source library that provides high-performance, easy-to-use data structures, and data analysis tools for Python. In this intermediate-level, hands-on course, learn how to use the pandas library and tools for data analysis and data structuring. Instructor Jonathan Fernandes dives into topics such as DataFrames, basic plotting, indexing, and groupby. To help you learn how to work with data more effectively, Jonathan takes you through a series of exercises that are based on the same large, public data set: the Olympic medal winners from 1896 to 2008. Umfang: 02:14:48.00
Inhalt: Decorators are an increasingly important feature in Python. They add functionality to an existing object without permanently modifying it. Being able to use decorators effectively is critical to working with larger Python projects and frameworks. In this course, Jonathan Fernandes explains what decorators are and why they are used so extensively in production projects. He explains how to solve common challenges associated with decorators, such as debugging; how to chain decorators; how to use decorators with classes; and how to access the arguments passed into decorated functions. Plus, find out how to use and debug decorators in the real world by examining decorators' role in the source code for the Flask microplatform. Umfang: 00:55:08
Inhalt: PyTorch is quickly becoming one of the most popular deep learning frameworks around, as well as a must-have skill in your artificial intelligence tool kit. It's gained admiration from industry leaders due to its deep integration with Python; its integration with top cloud platforms, including Amazon SageMaker and Google Cloud Platform; and its computational graphs that can be defined on the fly. In this course, join Jonathan Fernandes as he dives into the basics of deep learning using PyTorch. Starting with a working image recognition model, he shows how the different components fit and work in tandem-from tensors, loss functions, and autograd all the way to troubleshooting a PyTorch network. Umfang: 00:56:03.00
Inhalt: Bouncing back after a job loss can feel like both a professional and personal challenge. This course was designed to help you regain your footing. Join instructor Jonathan Fernandes as he provides guidance and actionable steps you can take to regain employment in the tech industry. Jonathan delves into popular industry topics such as multicloud and automation, providing strategies for assessing these and other key trends. He covers career options to consider, from staying in the same role to transitioning to a new career in tech. Plus, he shares steps you can take to land a job that better aligns with your professional goals-and look after your physical and mental health until that next job offer arrives. Umfang: 01:06:39
Inhalt: After its debut in 2017, PyTorch quickly became the tool of choice for many deep learning researchers. In this course, Jonathan Fernandes shows you how to leverage this popular machine learning framework for a similarly buzzworthy technique: transfer learning. Using a hands-on approach, Jonathan explains the basics of transfer learning, which enables you to leverage the pretrained parameters of an existing deep-learning model for other tasks. He then shows how to implement transfer learning for images using PyTorch, including how to create a fixed feature extractor and freeze neural network layers. Plus, find out about using learning rates and differential learning rates. Umfang: 00:58:35.00
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