$110 / month
4 calls per month (30min/call)
Unlimited Q&A via chat
Expect responses in 24 hours or less
Hands-on support
One-off sessions with Robin
One-off sessions are a great option if you’re looking for specific advice on a certain topic.
If you're looking for a mentor, and you're just not sure about how this all works – this one is for you. In a casual, informal introductory call, a mentor will introduce themselves, show you around the platform, explain how our mentorships work, and explain …
Having a good resume on hand when going on the job hunt is crucial, and will make your search a lot easier. Even if you're not looking for a new position right now, having an up-to-date CV that sells your experience to future potential employers …
Hi! My name is Robin. I have PhD and MS degrees in Computer Science and Electrical Engineering from UC Davis, where I was employed as the full instructor for the undergraduate Machine Learning Course. Afterwards, I completed a Machine Learning PostDoc at LLNL working on NIF during the recent world breakthrough achieving nuclear fusion. Throughout my university and postdoc research I not only published dozens of papers, but also developed many popular frameworks in Machine Learning, Deep Learning, Computer Vision, and Data Science.
I do any type of mentoring/consulting (eg. PhD research projects, industry); ask me what you need help with! I also offer 3 different series of lessons (Python, ML, and DL). Some topics covered include the following:
Machine Learning:
- KNN, Decision Trees (including random forest, bagging, boosting), PCA, SVM, Linear and Polynomial Models (including GLM), Neural Networks (all both code in sklearn and mathematical theory)
- Prepare data for ML using Pandas (handle NAs, missing values, data type issues etc.)
- Core concepts: classification/regression, dimensionality reduction, over/under-fitting, k-fold testing, proper results/accuracy presentation, parallelization, hyper-parameter optimization, class imbalance, scaling and handling outliers
Deep Learning:
- Apply DL models in PyTorch, Tensorflow, Keras, and Scikit-Learn
- Build full train/test/eval frameworks
- Understand how to choose loss functions, optimizers, and other DL hyperparameters
- Transfer Learning (and how to retrain or fine-tune off-the-shelf top models for other tasks)
- CNN, Transformers architecture breakdown and how to implement (eg. ViT, Swin, HuggingFace models etc.)
- Image classification, object detection, NLP
- GPU training, handling large tensor data, handling class imbalance
- Data transformations, augmentation
- Results analysis/reporting/plotting
Python:
- Basics
- LeetCode problems and Interview prep (eg. Trees, Linked Lists, time-complexity, sorting)
5 out of 5 stars
I have been working with Robin bi-weekly for many months now. I had began doing an online course/credential/bootcamp program but I am so glad I continued to work with Robin instead. Her course lessons aligned with the general ML algorithms I needed to learn and I aced my interview questions when they asked about them! It was so much easier to understand the theory with her examples and having opportunity to talk things out with her. Additionally, I am so grateful that her lesson notes taught me how to implement each algorithm in code as well. She also helped me with a python and LeetCode problems. (These were also in my interview and I did really well!) We normally do one session per week on python and one on ML. I didn’t know Python before working with her and now I’m a master at medium-hard LeetCode problems. She covered everything from basic to advanced data’s structures and algorithms in Python. It was much easier with someone to hold me accountable for writing quality code consistently. I learned Python much quicker than I could imagine! I’m really looking forward to continuing to learn deep learning with her while I work in my current SW engineering position. She has a lot of experience in the top models used and knows efficient techniques to optimize them based on her past research work.
5 out of 5 stars
Dr. Yancey is a cheerful, friendly, and kind tutor. She is currently working with my son on a machine-learning project that is looking at the problem of detecting forged photos. We like working with Robin as she not only explains machine learning but also explains the mathematical theory behind the models. She is patient and extremely well-prepared for the sessions with detailed slides, notes, and lectures. This makes sense as she created two machine-learning classes during her time at UC Davis and they are still using her content for the classes today! For anyone looking for her to tutor, she is very knowledgeable in machine learning and deep learning. She is also very skilled in Python and various machine-learning libraries such as PyTorch, Sklearn, Pandas, and NumPy. The only regret I have with Dr. Yancey is that I didn't hire her earlier!
5 out of 5 stars
Robin is skilled in Machine Learning and Deep Learning, and she's great at mentoring these subjects. She helped me not only with learning about Machine Learning but also in getting ready for job interviews. I had a session with her that made my interview feel easy, and I learned many important techniques in Machine Learning which will be very useful for my studies and for my future career in this field. Robin is experienced, kind, patient, and very supportive. If you're looking for a mentor in the Machine Learning area, I really recommend choosing her.
Notify me when Robin has new spots
We will send you a quick email if Robin has new open spots for mentorship, and only in that case!
