Want to hire ML developer? Then you should know!
How and where is ML used?
- Data Analysis: Predicting sales trends
- Natural Language Processing: Sentiment analysis of customer reviews
- Image Recognition: Identifying objects in photos
- Fraud Detection: Detecting fraudulent financial transactions
- Healthcare: Diagnosing diseases from medical images
- Recommendation Systems: Personalizing movie recommendations
- Autonomous Vehicles: Self-driving car navigation
- Virtual Assistants: Speech recognition for virtual assistants
- Predictive Maintenance: Anticipating equipment failures
- Financial Forecasting: Predicting stock prices
Compare Junior, Middle, Senior, and Expert/Team Lead ML Developer roles
Seniority Name | Years of experience | Responsibilities and activities | Average salary (USD/year) |
---|---|---|---|
Junior | 1-2 years |
| $60,000 |
Middle | 3-5 years |
| $80,000 |
Senior | 6-8 years |
| $100,000 |
Expert/Team Lead | 9+ years |
| $120,000 |
Quick Facts about ML.
- ML Software Development began its journey in 1959.
- Projects like chatbots and recommendation systems love using ML.
- Entry into ML requires a basic understanding of statistics.
- Deep Learning stands as the most popular related technology.
- In 2016, Google’s AI beat a Go world champion, shocking many!
TOP ML Related Technologies
- TensorFlow (Google)
- PyTorch (Facebook)
- Scikit-learn
- Keras
- Microsoft Cognitive Toolkit (CNTK)
- Theano
- Caffe
- MXNet
- Apache Singa
- Torch
Author: Google, 2015
Author: Facebook, 2016
Author: Microsoft, 2016
What are top ML instruments and tools?
- TensorFlow: Open-source ML library by Google, released in 2015
- Scikit-learn: Simple and efficient ML tools, released in 2007
- PyTorch: Developed by Facebook AI, released in 2016
- Keras: High-level neural networks API, released in 2015
- Theano: Python library for defining, optimizing, and evaluating mathematical expressions involving multi-dimensional arrays, released in 2007
- MXNet: Scalable and efficient deep learning framework, released in 2015
- Caffe: Deep learning framework made with expression, speed, and modularity in mind, released in 2014
Talk to Our Talent Expert
Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
Maria Lapko
Global Partnership Manager