Machine learning is transforming our world, from self-driving cars to personalized recommendations. It’s an exciting field with high demand for skilled professionals. Traditional machine-learning education can be expensive and time-consuming.
What is a Machine Learning (ML)?
Machine learning (ML) is a field of artificial intelligence (AI) that enables systems to learn and improve from experience without being explicitly programmed. It is a branch of computer science that deals with the ability of machines to learn from data, identify patterns, and make predictions or decisions without being explicitly programmed. In essence, machine learning algorithms are trained to find patterns and relationships in data, and then use those patterns to make predictions or decisions about new data.
Best uses of ML:
Machine learning is like a super-smart computer program that can learn from data and make predictions or decisions without being explicitly programmed.
- Image recognition: ML is used to train computers to identify objects and patterns in images and videos.
- Natural language processing (NLP): ML is used to train computers to understand and generate human language.
- Recommendation systems: ML is used to recommend products, movies, music, and other items to users based on their past behavior and preferences.
- Fraud detection: ML is used to detect fraudulent activity, such as credit card fraud and insurance fraud.
- Anomaly detection: ML is used to detect anomalies in data, such as outliers and unusual patterns.
- Predictive maintenance: ML is used to predict when machinery will fail so that it can be repaired or replaced before it breaks down.
- Personalized learning: ML is used to personalize learning experiences for students.
- Drug discovery: ML is used to accelerate the drug discovery process.
- Financial trading: ML is used to make financial trading decisions.
- Scientific research: ML is used to analyze large datasets and make new scientific discoveries.
These are just a few of the many ways that ML is being used to improve our lives. As machine learning technology continues to develop, we can expect to see even more innovative and transformative applications in the years to come.
Machine Learning (ML) job positions and annual salary:
| Job Title | Salary |
|---|---|
| Machine Learning Engineer | $160,000 |
| Data Scientist | $115,000 |
| Machine Learning Specialist | $102,000 |
| Machine Learning Architect | $180,000 |
| Machine Learning Consultant | $150,000 |
list of top company job certificate requirements for ML:
| Company | Job Title | Requirements |
|---|---|---|
| Professional Machine Learning Engineer | Bachelor’s degree in computer science, data science, or a related field | |
| Amazon | AWS Certified Machine Learning – Specialty | 2+ years of hands-on experience with AWS machine learning services |
| Microsoft | Azure AI Engineer Associate | 1+ years of experience in designing, developing, and deploying AI solutions in Azure |
| IBM | IBM Certified Data Scientist – Professional | 3+ years of experience in data science |
| Machine Learning Engineer | Bachelor’s degree in computer science, data science, or a related field | |
| Apple | Machine Learning Engineer | Bachelor’s degree in computer science, data science, or a related field |
These are just a few of the many companies that are hiring machine learning engineers. The specific requirements for each job will vary, but the general qualifications listed above are a good starting point.
11 Free online courses List of machine learning.
| No | Course Title | Platform | Duration | Level |
|---|---|---|---|---|
| 1 | Machine Learning for Everybody – Full Course | freeCodeCamp-YouTube | 3 hours | Beginners |
| 2 | Machine Learning | Machine Learning Tutorial For Beginners | Simplilearn-YouTube | 10 hours | Beginners |
| 3 | Machine Learning Tutorial | Edureka-YouTube | 10 hours | Beginners |
| 4 | Data Analytics Course | Intellipaat-YouTube | 3 hours | Beginners |
| 5 | Probabilistic Deep Learning with TensorFlow 2 | Coursera | 52 hours | Advanced |
| 6 | Introduction to Machine Learning | Udacity | 10 weeks | Advanced |
| 7 | MITx: Machine Learning with Python: from Linear Models to Deep Learning | edX | 15 weeks | Beginner |
| 8 | Machine Learning Foundations: A Case Study Approach | Coursera | 18 hours | Beginner |
| 9 | Introduction to Machine Learning for Data Science | Udemy | 5 hours | Beginner |
| 10 | ML Educational resources | DeepLearning.AI | 10 weeks | Beginner |
| 11 | DeepLearning.AI TensorFlow Developer Professional Certificate | Coursera | 2 months | Intermediate |
Free online courses offer several advantages over traditional learning methods, including self-pacing and interactive components.
Conclusion:
Embark on your machine learning journey with free online courses and empower yourself with the skills to navigate the data-driven future.
Thanks: Image by pch.vector on Freepik
