Bifalgorithm post

If I wanted to get a machine learning job in big tech, here are the projects that I'd actually build. The first thing that I'd build is a full end-to-end machine learning system. This would include the full pipeline of data collection, cleaning, feature engineering, model training, API deployment, and everything involved in the process. And a full end-to-end project like this could look something like a real estate price predictor or demand forecast system. And the real reason why we're building full systems is because companies don't hire you to build small models. They They want you to build full shipable systems. The next thing that I'd build is a full deep learning project with PyTorch. I would build something in the computer vision or NLP space, but it wouldn't be something like training a convolutional neural network. I'd build a full system around a deep learning application. Some examples of this would be a fully functional deployed object tracking system that works in real time or something like a resume job application matching system that works similar to the ATS and the final type of project that I would try to do is optimizing something you can do things like speeding up inference quantizing a model reducing latency and then deploying that with something like Docker and if you're interested in natural language processing you can actually take the exact same concept and try your hand at something like fine-tuning a large language model. And these three projects alone will put you ahead of 99% of other applicants because it shows that you can actually think like a machine learning engineer and you're not just their training models. And for more machine learning videos like this, follow for more

If I wanted to get a machine learning job in big tech, here are the projects that I'd actually build. The first thing that I'd build is a full end-to-end machi…