INTRODUCTION – Get Started With Databricks And Machine Learning In this module you will learn how to take advantage of PySpark’s machine learning library to construct important elements of a machine learning workflow. The module will teach you how to conduct exploratory data analysis and find the relevant insights and patterns from your data, how … Read more
Module 5: Manage Machine Learning Lifecycles And Fine Tune Models Almost every student is keenly aware of conditions students find themselves in to track learning processes using MLflow. Students also learn how to include modules from the machine learning library of Spark for hyperparameter tuning and model selection. This ensures that students understand how to … Read more
INTRODUCTION – Train A Distributed Neural Network And Serve Models With Azure Machine Learning In this section, you will learn to use Uber’s Horovod framework and Petastorm to run distributed deep learning training jobs using Spark with training datasets in Apache Parquet format. You will also explore how to register, package, and deploy trained models … Read more
INTRODUCTION – EXAM PREPARATION COURSE 1 This is the revisit of Course 1 content from Microsoft Azure Data Scientist Associate standard specialization. The course lays down concepts and skillsets introductory to using Azure with data science-essential. Data exploration, data preparation, and basic machine learning concepts, among other things, will be topics discussed in the review. … Read more
INTRODUCTION – Processing Data In Azure Data Bricks Azure Databricks offers several built-in SQL functions, but sometimes you might need to create your own functions – that is, User-Defined Functions or UDFs. In this course, you will discover how to register UDFs and invoke them, thereby extending the functionality of your SQL queries. You will … Read more
INTRODUCTION – Create A Regression Model With Azure Machine Learning Designer Regression is a supervised machine learning technique whose main objective is to predict numerical values based on data inputs. This module introduces regression model development using Azure Machine Learning Designer-an easy and user-friendly tool for developing and deploying machine learning models. Through hands-on training … Read more
INTRODUCTION – Explore Data And Create Models To Predict Numeric Values Data exploration and analysis are indeed vital and core portions of data science. Data scientists need to learn one of the general-purpose languages like Python to explore, visualize, and manipulate data. In this module, you will study how to use Python for these tasks. … Read more
INTRODUCTION – Train And Evaluate Classification And Clustering Models Classification is the machine learning method used to assign items to a predefined set of categories. In this module, you will be guided through the steps of building a model to predict categories using the state-of-the-art techniques. You are going to use the scikit-learn library of … Read more
INTRODUCTION – Train And Evaluate Deep Learning Models In this module, you will study basic principles of deep learning and learn how these principles help to understand the development of advanced neural network models. You will learn to build deep neural networks (DNNs) through popular frameworks such as PyTorch and TensorFlow. Parts of the module … Read more
INTRODUCTION – Working With Data In Azure Databricks Azure Databricks simplifies daily data handling like reading, writing, and querying data. This module manages large datasets and raw formats from different sources. You will learn about the different column-level transformations that can be performed using the DataFrame Column Class in Azure Databricks, such as sorting, filtering, … Read more