EDA was the first step followed by introducing an initial linear model and comparing it to other models at the end of the process. 7398 movie data collected from The Movie Database (TMDB) as part of a kaggle.com Box Office Prediction Competition. A train/test division is also given to bu...
How to Win a Data Science Competition: Learn from Top Kagglers:特征的预处理和生成(1) 本文根据:Overview - Feature Preprocessing and Generation with Respect to Models | Coursera及后面几个视频总结而来 Figure 1 废话少说,从Titanic数据集开始讲起 一行代表一个乘客的信息,一列表示一种数据(一个特征)。
In practice, however, we face a big constraint: time (deadline to deliver the model to clients or Kaggle competition). To add more complexity, single model never generates the best results, meaning we need to stack many models together to deliver great performance. How to effectively stack (...
You also have lots of useful public notebooks to peruse, an added advantage too Once you feel confident, you could try and form a team and then participate in a featured competition. This will give you an opportunity to share your ideas and hardware too. Hardware is an important factor in...
Kaggle competitions are a great way to test your skills and win prizes. If you're new to Kaggle, or if you're looking to improve your chances of success, here are a few tips on how to prepare for a Kaggle competition: Choose a competition that interests you: There are a variety of ...
How to Win a Data Science Competition: Learn from Top Kagglers”. The course mentions this link in its reading section. I was feeling stuck on a problem in Kaggle with no significant improvements with tweaking hyper-parameters and changing models. I was feeling the need to engineer mo...
performance, sometimes model even diverges on "unfortunate" seeds. During training, performance also wildly fluctuates from step to step. I can't just rely on pure luck (be on right seed and stop on right training step) to win the competition, so I had to take actions to reduce variance....
With Kaggle, new algorithms could be evaluated on real data. Which offer "shine" opportunity algorithms, and provide full details on sharing model performance results across competition data sets. After its appearance, theXGBoost Libraryquickly gained popularity. XGBoost is not a modern, special algor...
The Competition Process RecSys or Kaggle competitions work by asking users or teams to provide solutions to well-defined problems. Competitors download the training and test files, train models on the labeled training file, generate predictions on the test file, and then upload a prediction file ...
Celebrating a milestone — The real win was the priceless learning experience! Last month, I had the incredible honor of winning Singapore’s first ever GPT-4 Prompt Engineering competition, which brought together over 400 prompt-ly brilliant participants, organised by the Government Technology Agen...