Fix: question61 broken link

Author: danieldanielecki

README.md

@@ -138,7 +138,7 @@ We are so thankful for every contribution, which makes sure we can deliver top-n
 | 58  | [A manufacturer of car engines collects data from cars as they are being driven. The data collected includes timestamp, engine temperature, rotations per minute (RPM), and other sensor readings. The company wants to predict when an engine is going to have a problem, so it can notify drivers in advance to get engine maintenance. The engine data is loaded into a data lake for training. Which is the MOST suitable predictive model that can be deployed into production?](#a-manufacturer-of-car-engines-collects-data-from-cars-as-they-are-being-driven-the-data-collected-includes-timestamp-engine-temperature-rotations-per-minute-rpm-and-other-sensor-readings-the-company-wants-to-predict-when-an-engine-is-going-to-have-a-problem-so-it-can-notify-drivers-in-advance-to-get-engine-maintenance-the-engine-data-is-loaded-into-a-data-lake-for-training-which-is-the-most-suitable-predictive-model-that-can-be-deployed-into-production)
 | 59  | [A Machine Learning Specialist wants to bring a custom algorithm to Amazon SageMaker. The Specialist implements the algorithm in a Docker container supported by Amazon SageMaker. How should the Specialist package the Docker container so that Amazon SageMaker can launch the training correctly?](#a-machine-learning-specialist-wants-to-bring-a-custom-algorithm-to-amazon-sagemaker-the-specialist-implements-the-algorithm-in-a-docker-container-supported-by-amazon-sagemaker-how-should-the-specialist-package-the-docker-container-so-that-amazon-sagemaker-can-launch-the-training-correctly)
 | 60  | [A Data Scientist needs to analyze employment data. The dataset contains approximately 10 million observations on people across 10 different features. During the preliminary analysis, the Data Scientist notices that income and age distributions are not normal. While income levels shows a right skew as expected, with fewer individuals having a higher income, the age distribution also shows a right skew, with fewer older individuals participating in the workforce. Which feature transformations can the Data Scientist apply to fix the incorrectly skewed data? (Choose two.)](#a-data-scientist-needs-to-analyze-employment-data-the-dataset-contains-approximately-10-million-observations-on-people-across-10-different-features-during-the-preliminary-analysis-the-data-scientist-notices-that-income-and-age-distributions-are-not-normal-while-income-levels-shows-a-right-skew-as-expected-with-fewer-individuals-having-a-higher-income-the-age-distribution-also-shows-a-right-skew-with-fewer-older-individuals-participating-in-the-workforce-which-feature-transformations-can-the-data-scientist-apply-to-fix-the-incorrectly-skewed-data-choose-two)
-| 61  | [A web-based company wants to improve its conversion rate on its landing page. Using a large historical dataset of customer visits, the company has repeatedly trained a multi-class deep learning network algorithm on Amazon SageMaker. However, there is an overfitting problem: training data shows 90% accuracy in predictions, while test data shows 70% accuracy only. The company needs to boost the generalization of its model before deploying it into production to maximize conversions of visits to purchases. Which action is recommended to provide the HIGHEST accuracy model for the company's test and validation data?](#a-web-based-company-wants-to-improve-its-conversion-rate-on-its-landing-page-using-a-large-historical-dataset-of-customer-visits-the-company-has-repeatedly-trained-a-multi-class-deep-learning-network-algorithm-on-amazon-sagemaker-however-there-is-an-overfitting-problem-training-data-shows-90%25-accuracy-in-predictions-while-test-data-shows-70%25-accuracy-only-the-company-needs-to-boost-the-generalization-of-its-model-before-deploying-it-into-production-to-maximize-conversions-of-visits-to-purchases-which-action-is-recommended-to-provide-the-highest-accuracy-model-for-the-companys-test-and-validation-data)
+| 61  | [A web-based company wants to improve its conversion rate on its landing page. Using a large historical dataset of customer visits, the company has repeatedly trained a multi-class deep learning network algorithm on Amazon SageMaker. However, there is an overfitting problem: training data shows 90% accuracy in predictions, while test data shows 70% accuracy only. The company needs to boost the generalization of its model before deploying it into production to maximize conversions of visits to purchases. Which action is recommended to provide the HIGHEST accuracy model for the company's test and validation data?](#a-web-based-company-wants-to-improve-its-conversion-rate-on-its-landing-page-using-a-large-historical-dataset-of-customer-visits-the-company-has-repeatedly-trained-a-multi-class-deep-learning-network-algorithm-on-amazon-sagemaker-however-there-is-an-overfitting-problem-training-data-shows-90-accuracy-in-predictions-while-test-data-shows-70-accuracy-only-the-company-needs-to-boost-the-generalization-of-its-model-before-deploying-it-into-production-to-maximize-conversions-of-visits-to-purchases-which-action-is-recommended-to-provide-the-highest-accuracy-model-for-the-companys-test-and-validation-data)
 | 62  | [A real estate company wants to create a machine learning model for predicting housing prices based on a historical dataset. The dataset contains 32 features. Which model will meet the business requirement?](#a-real-estate-company-wants-to-create-a-machine-learning-model-for-predicting-housing-prices-based-on-a-historical-dataset-the-dataset-contains-32-features-which-model-will-meet-the-business-requirement)
 | 63  | [A Machine Learning Specialist is applying a linear least squares regression model to a dataset with 1,000 records and 50 features. Prior to training, the ML Specialist notices that two features are perfectly linearly dependent. Why could this be an issue for the linear least squares regression model?](#a-machine-learning-specialist-is-applying-a-linear-least-squares-regression-model-to-a-dataset-with-1000-records-and-50-features-prior-to-training-the-ml-specialist-notices-that-two-features-are-perfectly-linearly-dependent-why-could-this-be-an-issue-for-the-linear-least-squares-regression-model)
 | 64  | [Given the following confusion matrix for a movie classification model, what is the true class frequency for Romance and the predicted class frequency for Adventure?](#given-the-following-confusion-matrix-for-a-movie-classification-model-what-is-the-true-class-frequency-for-romance-and-the-predicted-class-frequency-for-adventure)