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Becoming a Machine Learning Specialist.pdf

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jashwanthmuthumula

Machine learning (ML) enables computers to learn from data without explicit programming, creating a high demand for specialists across various industries. Key skills include programming (Python or R), mathematics (statistics and probability), and familiarity with ML tools like TensorFlow and PyTorch. Educational paths involve degrees in computer or data science, online courses, and certifications, with job roles such as data scientist and ML engineer offering competitive salaries.

Education
Related topics:
Predictive Modeling • Deep Learning • Machine Learning Certification • Machine Learning Development
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MACHINE LEARNING SPECIALIST B E C O M I N G A @IABAC.ORG
INTRODUCTION What is Machine Learning (ML)? A way for computers to learn from data without being programmed. Why ML Specialist? High demand and great salaries in every industry. @IABAC.ORG
WHAT YOU NEED TO LEARN Programming: Python or R. Math: Statistics and Probability. ML Tools: TensorFlow, PyTorch, Scikit-learn. @IABAC.ORG
EDUCATIONAL OPTIONS Degrees: Computer Science or Data Science. Online Courses: Coursera, Udemy (Start with Andrew Ng's ML course). Certifications: Google or AWS ML certifications. @IABAC.ORG
CORE CONCEPTS TO KNOW Data Cleaning and Preprocessing. Types of ML: Supervised, Unsupervised, and Reinforcement Learning. Deep Learning: Neural Networks and CNNs. @IABAC.ORG
BUILD A PORTFOLIO Create projects like: Predicting prices (e.g., houses or stocks). Analyzing text for sentiment. Classifying images. Share work on GitHub or LinkedIn. @IABAC.ORG
JOBS AND SALARIES Job Roles: Data Scientist, ML Engineer, AI Developer. Current Salaries: Entry-level: ₹4,00,000 to ₹8,00,000 per annum. Experienced:₹15,00,000 to ₹25,00,000 per annum. @IABAC.ORG
HOW TO START Learn Python and Statistics. Take beginner ML courses online. Work on small projects. Network on LinkedIn or Kaggle. @IABAC.ORG
NETWORKING AND GROWTH Join ML groups on Kaggle, GitHub, or Reddit. Attend AI events and conferences. Follow experts and read blogs. @IABAC.ORG
CHALLENGES AND TIPS Challenges: Tough concepts, rapid updates in tools. Tips: Learn step by step. Keep practicing. Ask for help from mentors. @IABAC.ORG
FINAL THOUGHTS ML is an exciting and fast-growing field. Start small, learn continuously, and grow your skills. The future is bright for ML specialists! @IABAC.ORG
THANK YOU @IABAC.ORG

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Becoming a Machine Learning Specialist.pdf

  • 1. MACHINE LEARNING SPECIALIST B E C O M I N G A @IABAC.ORG
  • 2. INTRODUCTION What is Machine Learning (ML)? A way for computers to learn from data without being programmed. Why ML Specialist? High demand and great salaries in every industry. @IABAC.ORG
  • 3. WHAT YOU NEED TO LEARN Programming: Python or R. Math: Statistics and Probability. ML Tools: TensorFlow, PyTorch, Scikit-learn. @IABAC.ORG
  • 4. EDUCATIONAL OPTIONS Degrees: Computer Science or Data Science. Online Courses: Coursera, Udemy (Start with Andrew Ng's ML course). Certifications: Google or AWS ML certifications. @IABAC.ORG
  • 5. CORE CONCEPTS TO KNOW Data Cleaning and Preprocessing. Types of ML: Supervised, Unsupervised, and Reinforcement Learning. Deep Learning: Neural Networks and CNNs. @IABAC.ORG
  • 6. BUILD A PORTFOLIO Create projects like: Predicting prices (e.g., houses or stocks). Analyzing text for sentiment. Classifying images. Share work on GitHub or LinkedIn. @IABAC.ORG
  • 7. JOBS AND SALARIES Job Roles: Data Scientist, ML Engineer, AI Developer. Current Salaries: Entry-level: ₹4,00,000 to ₹8,00,000 per annum. Experienced:₹15,00,000 to ₹25,00,000 per annum. @IABAC.ORG
  • 8. HOW TO START Learn Python and Statistics. Take beginner ML courses online. Work on small projects. Network on LinkedIn or Kaggle. @IABAC.ORG
  • 9. NETWORKING AND GROWTH Join ML groups on Kaggle, GitHub, or Reddit. Attend AI events and conferences. Follow experts and read blogs. @IABAC.ORG
  • 10. CHALLENGES AND TIPS Challenges: Tough concepts, rapid updates in tools. Tips: Learn step by step. Keep practicing. Ask for help from mentors. @IABAC.ORG
  • 11. FINAL THOUGHTS ML is an exciting and fast-growing field. Start small, learn continuously, and grow your skills. The future is bright for ML specialists! @IABAC.ORG