Become a Machine Learning expert. Put your machine learning knowledge to work, and expand your production engineering capabilities and begin to turn your ideas into realities.
Navigate to each course's week folder. Example C1-..../Week2 and execute:
# Enter the name of the environment when prompted
../../create_new_env.sh
- Check the
requirements.txtfor each file. Also, see if we can use one environment for every week. Then remove the need for conda setup for individual week.
Each course is spread out in weeks, and are made up of video slides, lab sessions, quizzes, assignments, related course materials, code and data
- Ungraded Lab: Simple Feature Engineering
- Ungraded Lab: Feature Engineering Pipeline
- Ungraded Lab: Feature Selection
- Ungraded Lab: Feature Engineering with Weather Data
- Ungraded Lab: Feature Engineering with Accelerometer Data
- Ungraded Lab: Feature Engineering with Images
- Ungraded lab: Manual Feature Engineering
- Ungraded lab: Algorithmic Dimensionality Reduction
- Ungraded Lab: Quantization and Pruning
- Ungraded lab: Distributed Strategies with TF and Keras
- Ungraded Lab: Knowledge Distillation
- Ungraded lab: Distributed Strategies with TF and Keras
- Ungraded Lab: TensorFlow Model Analysis
- Ungraded Lab: Model Analysis with TFX Evaluator
- Ungraded Lab: Fairness Indicators
The solutions presented are intended to serve as reference for other learners who enroll in this course. Solutions are adapted from John Moses' repo.