Fix: question48 broken link

Author: danieldanielecki

README.md

@@ -125,7 +125,7 @@ We are so thankful for every contribution, which makes sure we can deliver top-n
 | 45  | [A Data Scientist is building a Linear Regression model and will use resulting p-values to evaluate the statistical significance of each coefficient. Upon inspection of the dataset, the Data Scientist discovers that most of the features are normally distributed. The plot of one feature in the dataset is shown in the graphic. What transformation should the Data Scientist apply to satisfy the statistical assumptions of the Linear Regression model?](#a-data-scientist-is-building-a-linear-regression-model-and-will-use-resulting-p-values-to-evaluate-the-statistical-significance-of-each-coefficient-upon-inspection-of-the-dataset-the-data-scientist-discovers-that-most-of-the-features-are-normally-distributed-the-plot-of-one-feature-in-the-dataset-is-shown-in-the-graphic-what-transformation-should-the-data-scientist-apply-to-satisfy-the-statistical-assumptions-of-the-linear-regression-model)
 | 46  | [A technology startup is using complex deep neural networks and GPU compute to recommend the company's products to its existing customers based upon each customer's habits and interactions. The solution currently pulls each dataset from an Amazon S3 bucket before loading the data into a TensorFlow model pulled from the company's Git repository that runs locally. This job then runs for several hours while continually outputting its progress to the same S3 bucket. The job can be paused, restarted, and continued at any time in the event of a failure, and is run from a central queue. Senior managers are concerned about the complexity of the solution's resource management and the costs involved in repeating the process regularly. They ask for the workload to the automated so it runs once a week, starting Monday and completing by the close of business Friday. Which architecture should be used to scale the solution at the lowest cost?](#a-technology-startup-is-using-complex-deep-neural-networks-and-gpu-compute-to-recommend-the-companys-products-to-its-existing-customers-based-upon-each-customers-habits-and-interactions-the-solution-currently-pulls-each-dataset-from-an-amazon-s3-bucket-before-loading-the-data-into-a-tensorflow-model-pulled-from-the-companys-git-repository-that-runs-locally-this-job-then-runs-for-several-hours-while-continually-outputting-its-progress-to-the-same-s3-bucket-the-job-can-be-paused-restarted-and-continued-at-any-time-in-the-event-of-a-failure-and-is-run-from-a-central-queue-senior-managers-are-concerned-about-the-complexity-of-the-solutions-resource-management-and-the-costs-involved-in-repeating-the-process-regularly-they-ask-for-the-workload-to-the-automated-so-it-runs-once-a-week-starting-monday-and-completing-by-the-close-of-business-friday-which-architecture-should-be-used-to-scale-the-solution-at-the-lowest-cost)
 | 47  | [A Machine Learning Specialist prepared the following graph displaying the results of K-means for k = [1..10]. Considering the graph, what is a reasonable selection for the optimal choice of k?](#a-machine-learning-specialist-prepared-the-following-graph-displaying-the-results-of-k-means-for-k--110-considering-the-graph-what-is-a-reasonable-selection-for-the-optimal-choice-of-k)
-| 48  | [A machine learning specialist works for a fruit processing company and needs to build a system that categorizes apples into three types. The specialist has collected a dataset that contains 150 images for each type of apple and applied transfer learning on a neural network that was pretrained on ImageNet with this dataset. The company requires at least 85% accuracy to make use of the model. After an exhaustive grid search, the optimal hyperparameters produced the following: 68% accuracy on the training set. 67% accuracy on the validation set. What can the machine learning specialist do to improve the system's accuracy?](#a-machine-learning-specialist-works-for-a-fruit-processing-company-and-needs-to-build-a-system-that-categorizes-apples-into-three-types-the-specialist-has-collected-a-dataset-that-contains-150-images-for-each-type-of-apple-and-applied-transfer-learning-on-a-neural-network-that-was-pretrained-on-imagenet-with-this-dataset-the-company-requires-at-least-85%25-accuracy-to-make-use-of-the-model-after-an-exhaustive-grid-search-the-optimal-hyperparameters-produced-the-following-68%25-accuracy-on-the-training-set-67%25-accuracy-on-the-validation-set-what-can-the-machine-learning-specialist-do-to-improve-the-systems-accuracy)
+| 48  | [A machine learning specialist works for a fruit processing company and needs to build a system that categorizes apples into three types. The specialist has collected a dataset that contains 150 images for each type of apple and applied transfer learning on a neural network that was pretrained on ImageNet with this dataset. The company requires at least 85% accuracy to make use of the model. After an exhaustive grid search, the optimal hyperparameters produced the following: 68% accuracy on the training set. 67% accuracy on the validation set. What can the machine learning specialist do to improve the system's accuracy?](#a-machine-learning-specialist-works-for-a-fruit-processing-company-and-needs-to-build-a-system-that-categorizes-apples-into-three-types-the-specialist-has-collected-a-dataset-that-contains-150-images-for-each-type-of-apple-and-applied-transfer-learning-on-a-neural-network-that-was-pretrained-on-imagenet-with-this-dataset-the-company-requires-at-least-85-accuracy-to-make-use-of-the-model-after-an-exhaustive-grid-search-the-optimal-hyperparameters-produced-the-following-68-accuracy-on-the-training-set-67-accuracy-on-the-validation-set-what-can-the-machine-learning-specialist-do-to-improve-the-systems-accuracy)
 | 49  | [A company uses camera images of the tops of items displayed on store shelves to determine which items were removed and which ones still remain. After several hours of data labeling, the company has a total of 1,000 hand-labeled images covering 10 distinct items. The training results were poor. Which machine learning approach fulfills the company's long-term needs?](#a-company-uses-camera-images-of-the-tops-of-items-displayed-on-store-shelves-to-determine-which-items-were-removed-and-which-ones-still-remain-after-several-hours-of-data-labeling-the-company-has-a-total-of-1000-hand-labeled-images-covering-10-distinct-items-the-training-results-were-poor-which-machine-learning-approach-fulfills-the-companys-long-term-needs)
 | 50  | [A Data Scientist is developing a binary classifier to predict whether a patient has a particular disease on a series of test results. The Data Scientist has data on 400 patients randomly selected from the population. The disease is seen in 3% of the population. Which cross-validation strategy should the Data Scientist adopt?](#a-data-scientist-is-developing-a-binary-classifier-to-predict-whether-a-patient-has-a-particular-disease-on-a-series-of-test-results-the-data-scientist-has-data-on-400-patients-randomly-selected-from-the-population-the-disease-is-seen-in-3%25-of-the-population-which-cross-validation-strategy-should-the-data-scientist-adopt)
 | 51  | [A Machine Learning Specialist is attempting to build a Linear Regression model. Given the displayed residual plot only, what is the MOST likely problem with the model?](#a-machine-learning-specialist-is-attempting-to-build-a-linear-regression-model-given-the-displayed-residual-plot-only-what-is-the-most-likely-problem-with-the-model)