/data_science

AI, Machine learning, Neural networks, Deep learning: doing hands-on experience by Python, TensorFlow through IBM DS, Deeplearning.AI courses and others

Primary LanguageJupyter Notebook

Data_science

10/ Kaggle AI report 2023, link URL

9/ 2023 - ML_AI_Data Landscape: the definitive market map of companies and products in machine learning, artificial intelligence and data, compiled by FirstMark.

8/ AI for Good Specialization: AI and Public Health, AI and Climate Change, AI and Disaster Management.

7/ III.4 Machine Learning_ Theory and Hands-on Practice with Python Specialization:

  • Introduction to Machine Learning: Supervised Learning
  • Unsupervised Algorithms in Machine Learning
  • Introduction to Deep Learning

6/ IBM Data Science-(certificate), Credly URL

IBM Data SCIENCE

5/ Deep learning-(certificate)

Deep Learning certificate

4/ DeepLearning.AI TensorFlow Developer-(certificate)

DeepLearning.AI TensorFlow Developer certificate

3/ TensorFlow: Data & Deployment-(certificate)

2/ TensorFlow: Advanced Techniques-(certificate)

1/ Machine Learning Engineering for Production (MLOps)

  • Identify the key components of the ML lifecycle and pipeline and compare the ML modeling iterative cycle with the ML product deployment cycle.

  • Understand how performance on a small set of disproportionately important examples may be more crucial than performance on the majority of examples.

  • Solve problems for structured, unstructured, small, and big data. Understand why label consistency is essential and how you can improve it.