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You have written unit tests for a Kubeflow Pipeline that require custom libraries. You want to automate the execution of unit tests with each new push to your development branch in Cloud Source Repositories. What should you do? A. Write a script that sequenti...

You are training an LSTM-based model on AI Platform to summarize text using the following job submission script: gcloud ai-platform jobs submit training $JOB_NAME \ --package-path $TRAINER_PACKAGE_PATH \ --module-name $MAIN_TRAINER_MODULE \ --job-dir $JOB_...

You have deployed multiple versions of an image classification model on AI Platform. You want to monitor the performance of the model versions over time. How should you perform this comparison? A. Compare the loss performance for each model on a held-out data...

You trained a text classification model. You have the following SignatureDefs: You started a TensorFlow-serving component server and tried to send an HTTP request to get a prediction using: headers = {"content-type": "application/json"} json_response = requ...

Your organization's call center has asked you to develop a model that analyzes customer sentiments in each call. The call center receives over one million calls daily, and data is stored in Cloud Storage. The data collected must not leave the region in which t...

You are an ML engineer at a global shoe store. You manage the ML models for the company's website. You are asked to build a model that will recommend new products to the user based on their purchase behavior and similarity with other users. What should you do?...

You work for a social media company. You need to detect whether posted images contain cars. Each training example is a member of exactly one class. You have trained an object detection neural network and deployed the model version to AI Platform Prediction for...

You are responsible for building a unified analytics environment across a variety of on-premises data marts. Your company is experiencing data quality and security challenges when integrating data across the servers, caused by the use of a wide range of discon...

You are an ML engineer at a regulated insurance company. You are asked to develop an insurance approval model that accepts or rejects insurance applications from potential customers. What factors should you consider before building the model? A. Redaction, re...

You are training a Resnet model on AI Platform using TPUs to visually categorize types of defects in automobile engines. You capture the training profile using theCloud TPU profiler plugin and observe that it is highly input-bound. You want to reduce the bottl...

In statistics, exploratory data analysis or EDA is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond...

How is EDA used in machine learning? As we mentioned, the exploratory data analysis approach does not impose deterministic or probabilistic models on the data. On the contrary; the EDA approach allows the data to suggest admissible models that best fit the d...

You have trained a model on a dataset that required computationally expensive preprocessing operations. You need to execute the same preprocessing at prediction time. You deployed the model on AI Platform for high-throughput online prediction. Which architectu...

Your team trained and tested a DNN regression model with good results. Six months after deployment, the model is performing poorly due to a change in the distribution of the input data. How should you address the input differences in production? A. Create ale...

You need to train a computer vision model that predicts the type of government ID present in a given image using a GPU-powered virtual machine on Compute Engine. You use the following parameters: Optimizer: SGD Image shape = 224ֳ—224 Batch size = 64 Epochs...

You developed an ML model with AI Platform, and you want to move it to production. You serve a few thousand queries per second and are experiencing latency issues. Incoming requests are served by a load balancer that distributes them across multiple Kubeflow C...

The purpose of an EDA is to find insights which will serve for data cleaning, preparation, or transformation, which will ultimately be used in a machine learning algorithm. We use data analysis and data visualization at every step of the machine learning pro...

In this lab, you will perform exploratory data analysis on the U.S.A housing data set and the New York taxi fare data set as well. You will create Seaborn plots for exploratory data analysis in Python and BigQuery. First, you'll learn how to analyze a Pandas...

Overview This lab is in introduction to linear regression using Python and Scikit-Learn. This lab serves as a foundation for more complex algorithms and machine learning models that you will encounter in the course. We will train a linear regression model to ...

1. Which of the following is not a component of Exploratory Data Analysis? A. Statistical Analysis and Clustering B. Hyperparameter tuning C. Anomaly Detection D. Accounting and Summarizing   2. What are the objectives of exploratory data analysis? A. U...