Python ML
Infosys Bengaluru East, Karnataka, India
Job Description
"Embark on a journey to become a proficient Python Machine Learning (ML) expert at Infosys, where innovation meets technology."
In this rapidly evolving digital landscape, Machine Learning has emerged as a game-changer for businesses across various sectors, including Financial Services. As a Python ML expert at Infosys, you will play a pivotal role in driving business growth through data-driven insights and cutting-edge solutions.
At Infosys, we seek individuals who are not only passionate about technology but also possess strong business acumen, excellent communication skills, and a keen eye for domain expertise. If you're a self-driven, intellectually curious, and tech-savvy individual, this role is perfect for you.
Why you should learn this:
With the increasing adoption of AI and ML across industries, the demand for skilled Python ML professionals is skyrocketing, making it an ideal time to upskill or reskill.
Expected Salary: $100,000 - $150,000 per annum (average salary range for Python ML experts in India)
How it works:
- Step 1: Gain a solid understanding of Python programming fundamentals, including data structures, file operations, and object-oriented programming.
- Step 2: Familiarize yourself with popular ML libraries and frameworks, such as TensorFlow, Keras, and scikit-learn, and learn to implement them for real-world problems.
Core Concepts to Master
Supervised Learning
Supervised learning involves training a model on labeled data to make predictions on new, unseen data. This type of learning is widely used in classification and regression tasks.
Unsupervised Learning
Unsupervised learning involves training a model on unlabeled data to identify patterns or relationships. This type of learning is widely used in clustering and dimensionality reduction tasks.
Deep Learning
Deep learning involves training a model on a large dataset using multiple layers of artificial neural networks. This type of learning is widely used in computer vision and natural language processing tasks.
Interview Questions (Beginner)
- What is Machine Learning, and how is it different from traditional programming?
- Explain the concept of supervised learning and provide an example.
- How do you handle imbalanced datasets in a classification problem?
Job Overview
Advance Questions
- • Design a neural network architecture to solve a real-world problem.
- • Explain the concept of transfer learning and provide an example.
- • How do you optimize the hyperparameters of a machine learning model?