Predictive Modeling & Deep Learning

What you will learn

Build intelligent algorithms that can self-correct and self-heal. Discover methods to interpret real-time analysis of data to automate andincrease efficiency across all business domains, setting the stage for meaningful AI that moves from reactive to predictive. Sign up for free access today and sample 7,151 courses, 110+ Practice Labs, and 10+ live online bootcamps across 67 subjects.

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Applied Deep Learning: Unsupervised Data

Course | 1h 28m 28s

Explore deep learning and the implementation of deep learning-based frameworks for NLP and audio data analysis. Discover the architectures of recurrent neural network, the challenges associated with unsupervised learning, prominent statistical classification models, and the differences between generative classifiers and discriminative classifiers. The different types of generative models, the characteristics of the different classes of artificial neural networks, and the essential capabilities and variants of ResNet are also covered. We will also explore the roles of Encoders and Autoencoders in Deep learning implementations and work with PixelCNN.

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Predictive Modeling: Implementing Predictive Models Using Visualizations

Course | 41m 40s

Explore how to work with feature selection, general classes of feature selection algorithms, and predictive modeling best practices. Discover how to implement predictive models with scatter plots, boxplots, and crosstabs using Python.

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LAB: Deep Learning Programming with Python

Practice Lab | 8h

Perform DL programming tasks with Python, such as performing series expansion and calculus, and work with Tensorflow and scikit-image. Then, test your skills by answering assessment questions after loading a data set for hierarchical clustering and k-means clustering, and train a model using random forests and gradient boosting. This lab provides access to several tools commonly used in machine learning, including Microsoft Excel 2016, Visual Studio Code, Anaconda, Jupyter Notebook + JupyterHub, Pandas, NumPy, SiPy, Seaborn Library, and Spyder IDE.

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What are digital skills? A comprehensive definition

The aim of this guide is to give you a large and diverse shopping list of digital skills so that you can pick and choose to create the ideal list that helps you meet your organisational goals, which…

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A Set of Best Practices for Targeting, Aligning and Measuring Learning

How do you show measurable results on your learning investments? Download this paper for a set of best practices for identifying learning needs that support business priorities, align a solution and…

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Delivering on Data Science and AI for Competitive Edge

Data science represents a vital ingredient in enabling companies to better understand their customers, build meaningful products, offer innovative services and optimize operations to improve ROI.…

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