u/Legal_Low_285

I have an interview for the Tesla Optimus team as an intern specifically doing machine learning and reinforcement learning stuff. I've not been told what the interview will be about, only that I will be programming in Python. I've been preparing for it through a number of different ways:

• Implementing various algorithms (MLP, various optimizers and regularization methods, CNN, forward pass, backward pass, etc.) using just Numpy and PyTorch from scratch with a heavy emphasis on vectorizing everything
• Going over the math for all the major ML architectures (MLP, CNN, RNN, Transformer, etc)
• Going over the math for all popular RL algorithms (DQN, PPO, SAC)
• Making sure I know everything on my resume

Is there anything else that I should be doing or looking at? I haven't really done any LeetCode as I assumed it wouldn't focus on my LeetCode skills, should I brush up on that as well? Any tips would be greatly appreciated!

I have an interview for the Tesla Optimus team as an intern specifically doing machine learning and reinforcement learning stuff. I've not been told what the interview will be about, only that I will be programming in Python. I've been preparing for it through a number of different ways:

• Implementing various algorithms (MLP, various optimizers and regularization methods, CNN, forward pass, backward pass, etc.) using just Numpy and PyTorch from scratch with a heavy emphasis on vectorizing everything
• Going over the math for all the major ML architectures (MLP, CNN, RNN, Transformer, etc)
• Going over the math for all popular RL algorithms (DQN, PPO, SAC)
• Making sure I know everything on my resume

Is there anything else that I should be doing or looking at? I haven't really done any LeetCode as I assumed it wouldn't focus on my LeetCode skills, should I brush up on that as well? Any tips would be greatly appreciated!

I have an interview for the Tesla Optimus team as an intern specifically doing machine learning and reinforcement learning stuff. I've not been told what the interview will be about, only that I will be programming in Python. I've been preparing for it through a number of different ways:

• Implementing various algorithms (MLP, various optimizers and regularization methods, CNN, forward pass, backward pass, etc.) using just Numpy and PyTorch from scratch with a heavy emphasis on vectorizing everything
• Going over the math for all the major ML architectures (MLP, CNN, RNN, Transformer, etc)
• Going over the math for all popular RL algorithms (DQN, PPO, SAC)
• Making sure I know everything on my resume

Is there anything else that I should be doing or looking at? I haven't really done any LeetCode as I assumed it wouldn't focus on my LeetCode skills, should I brush up on that as well? Any tips would be greatly appreciated!