For years, people started to debate over technology – whether it is a boon or bane. But, to me, at least, technology has helped people evolve their simple lifestyles into more productive ones. So, I guess technology is a thing that makes everyone’s life more accessible than ever, but it isn’t given the many credits that it deserves. Of course, it has its negative aspects which should not be forgotten either. Regardless of the consequences, the advancements here never stop.
This article focuses on the top deep learning questions being asked in machine learning interviews which are one aspect of technology nowadays. To put it in simple words;
“Technology is as Useful as a Servant, But a Dangerous Master “
What are Deep Learning & Machine Learning?
Deep learning :
Deep learning is more like an amalgamation of machine learning and Artificial Intelligence (AI) that imitates the way humans gain certain kinds of knowledge. Even Though old machine learning techniques are linear, these are characterized in the process of increasing complexity and abstraction. For instance, self-driving amenities in a car.
Deep Q-learning:
Deep Q-learning, also known as Deep reinforcement learning, is a subfield of machine learning techniques that combine reinforcement and deep understanding. It is a compelling yet straightforward method to create a cheat sheet for our agent. This helps the agent figure out the exact action that’s needed to be performed. An application of this system is widespread in the network of gaming.
Machine learning :
Machine learning is a part of Artificial Intelligence (AI) and computer science that allows software applications to become a prolific outcome predictor, even without being programmed to do so. They use historical data to predict the new values of output. Recognition of images through scanning with the black and white pixels is an excellent example of this. This technology is used to scan if the X-rays detect cancerous tissue, thus taking a primary spot in medical diagnosis.
Career & Scope for Machine Learning:
Machine learning is an outstanding choice for your career if you are fascinated by data, automation, and algorithms. It has quite a lot of opportunities that provide an adequate salary to the employees.
According to the World Economic Forum, by 2025, automation, AI, and machine learning will count for about 95 million jobs worldwide.
What are the jobs offered for machine learning?
As machine learning keeps growing day by day, so do the jobs associated with it. These are the jobs related to machine learning:
- Software developer: Software developers owe the skills needed to develop programs and look into the creations. A career as a software developer is a fast-growing field that’s becoming more and more essential for many companies.
Annual salary: $58,000 to $120,000.
- Machine learning engineer: A machine learning expert uses programming languages like Python, Java, Scala, etc., to run experiments with the appropriate machine learning libraries. Their job is to make sure that data science code is readily available, scalable, and easy to maintain. These engineers are responsible for taking away different comprehensions that are present in most machine learning tasks.
Salary offered: $69,000 to $150,000+
- Human-centered machine learning designer: Some places where you’ll find human-centered machine learning designers’ applications are on pages recommended by organizations like Netflix and how Amazon gets to know your preferences in purchases and lists them out to you on various sites. Banks use it to sort through financial transfers to see which ones are fraudulent.
Annual salary: $69,000 to $125,000.
- Data scientist: Data scientists analyze large amounts of data to make valuable insights on where taking actions is possible and necessary. They work in both business and IT fields, thus making them a valuable employee.
Salary expected: $87,000 to $150,000+
- Computational linguistic: If you are a person that loves linguistics and technology, then this job is just meant for you to pick up. As voice recognition gets more popular in technology, so do the jobs that make this software work.
Expected salary: $81,000 to $106,000.
Top Questions asked in Deep Learning Interviews:
To prepare for an interview in deep learning, these are the questions to be gone through:
- What is Deep Learning?
- What is a Neural Network?
- What is a Multi-layer Perceptron(MLP), and where do we use it?
- Explain Data Normalization and do we need it?
- What is the Boltzmann Machine?
- Explain the role of Activation Functions under a Neural Network?
- What Is the Cost Function?
- What do you understand about the term ‘Backpropagation’?
- What is Gradient Descent?
- What are the differences between an FFN Network and RNN Network?
- What are the Softmax and ReLU functions?
- What Are Hyperparameters?
- What is the outcome if the learning rate is decreased or increased substantially?
- What Is the Difference between Batch Gradient Descent and Stochastic Gradient Descent?
- What Is Dropout and Batch Normalization?
- How are weights initialized in a Network?
- Explain Underfitting and Overfitting. How can we combat them?
- What are the different layers on CNN?
- How does an LSTM Network work?
- What is Pooling on CNN, and how does it work?
- What are Vanishing and Exploding Gradients?
Conclusion:
“Confidence is the Most attractive thing one can possess.”
With that being said, the above-listed form a part of fundamental questions that might be asked in most of the top machine learning interviews. Anyhow, I reckon having the best core knowledge would help you overcome any discussions. So, educate yourself in the best way in the subject and be confident. Good luck with the interview.
