If you’re reading this, you might be gearing up for a Machine Learning internship at Pinterest or considering applying. As someone who recently went through the process, I wanted to share my experience with the Pinterest ML Intern Online Assessment (OA) preparation. Whether you’re new to machine learning or already familiar with the basics, this guide will help you understand how to approach the OA and the steps I took to prepare effectively.
1. Understand the Format of the OA
Before diving into preparation, it’s essential to understand the OA format. The assessment typically includes:
- Coding Problems: These are algorithmic problems that test your data structures and algorithm knowledge. Some of these may involve machine learning concepts or require implementing algorithms from scratch.
- Machine Learning Problems: These focus on your understanding of machine learning algorithms, such as linear regression, decision trees, clustering, and classification. You might be asked to solve problems or analyze datasets.
- Multiple-Choice Questions: These questions can test your theoretical knowledge of machine learning, algorithms, and statistical concepts.
2. Brush Up on Key Concepts
I began my preparation by reviewing key machine learning concepts and algorithms. Here’s what I focused on:
- Supervised Learning: Understand the difference between regression and classification problems. Be comfortable with algorithms like linear regression, logistic regression, decision trees, k-nearest neighbors, and support vector machines (SVM).
- Unsupervised Learning: Learn about clustering algorithms such as k-means and hierarchical clustering. Make sure you understand dimensionality reduction techniques like PCA (Principal Component Analysis).
- Deep Learning Basics: While the focus of the OA isn’t on deep learning, it’s still a good idea to be familiar with concepts like neural networks and backpropagation, especially if the role you’re applying for may involve these techniques.
- Feature Engineering and Model Evaluation: Be familiar with techniques to preprocess data, handle missing values, and engineer features. Also, review evaluation metrics like accuracy, precision, recall, F1-score, and AUC-ROC.
3. Practice Coding Problems
Coding problems are a significant part of the Pinterest ML Intern OA, so I spent a lot of time practicing algorithms and data structures. Here’s where I focused my attention:
- Data Structures: Make sure you understand arrays, linked lists, stacks, queues, heaps, hash maps, and graphs. These are the building blocks for solving many algorithmic problems.
- Algorithms: Focus on sorting algorithms, dynamic programming, greedy algorithms, and graph algorithms. For example, know how to implement depth-first search (DFS) and breadth-first search (BFS).
- LeetCode: LeetCode was my go-to platform for practicing coding problems. I made sure to solve problems tagged with “Machine Learning,” “Array,” “Dynamic Programming,” and “Graph.” Start with easier problems and gradually move to medium and hard problems.
- Time and Space Complexity: While solving coding problems, always think about the time and space complexity of your solution. Being able to optimize your code is critical.
4. Learn About Pinterest’s Machine Learning Stack
It’s always beneficial to know about the company’s tech stack, as this shows your interest and understanding of how they work. Pinterest uses machine learning in various areas like personalized recommendations, ad targeting, and content curation. Understanding the role machine learning plays at Pinterest can give you insights into the kind of problems you might encounter.
- Pandas & NumPy: Familiarize yourself with these Python libraries as they’re commonly used in machine learning tasks, especially for data preprocessing and analysis.
- Scikit-Learn: While you might not have to use it directly during the OA, understanding how to apply scikit-learn for implementing machine learning algorithms will help you solve problems efficiently.
5. Mock Interviews and Time Management
To ensure I was ready for the actual OA, I did mock interviews with friends and used platforms like Pramp and Interviewing.io. This helped me get used to solving problems under time constraints, which is essential for the OA. I also timed myself while practicing coding problems on LeetCode to simulate the real exam environment.
6. Focus on Problem Solving
In my experience, the most important part of the OA is problem-solving. The ability to break down a problem, write clean code, and debug effectively is what matters most. During the OA, I took the following steps:
- Understand the Problem: Take a few minutes to read the problem carefully. Make sure you understand the inputs, outputs, and constraints before starting.
- Plan Your Solution: Think about the best data structure or algorithm to solve the problem. Write down a plan before jumping into coding.
- Edge Cases: Always consider edge cases, like empty inputs or large values, and handle them in your code.
7. Stay Calm and Confident
Lastly, stay calm during the assessment. It can be tempting to rush through problems, but taking your time to think clearly will help you perform better. Don’t get stuck on one problem for too long. If you’re struggling, move on and come back to it later. Read More
