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Kaggle是一个流行的数据科学竞赛平台。 GitHub 入门操作指南和Kaggle 入门操作指南,适合于学习过MachineLearning(机器学习实战)的小盆友 Kaggle 已被 Google 收购,请参阅《谷歌收购 Kaggle 为什么会震动三界(AI、机器学习、数据科学界)》 Note: 号外号外kaggle组队开始啦 比赛收集平台:https://github.com/iphysresearch...
DataScience projects for learning : Kaggle challenges, Object Recognition, Parsing, etc. pythonchallengemachine-learninghackerrankkaggle UpdatedJan 13, 2023 Jupyter Notebook Load more… Add a description, image, and links to thekaggletopic page so that developers can more easily learn about it. ...
Intro to Machine Learning 3 hours to complete Learn the core ideas in machine learning, and build your first models. Pandas 4 hours to complete Solve short hands-on challenges to perfect your data manipulation skills. Build your ML skills in a supportive and helpful community ...
12月拿到自己的第一块Kaggle奖牌 短期内读完Abhishek Thakur的Approaching (Almost) Any Machine Learning Problem并且发博客记录https://github.com/abhishekkrthakur/approachingalmost 12月至少发21篇博客 每天保持八小时的学习时间 Approaching categorical variables(实验部分) ...
Kaggle 的回答和文章，然而逐渐发现大部分文章中提到的经验和技巧是针对传统machine learning类比赛的，对...
input_text = "Write me a poem about Machine Learning." input_ids = tokenizer(input_text, return_tensors="pt").to("cuda") outputs = model.generate(**input_ids) print(tokenizer.decode(outputs[0])) 不过最方便的还是直接线上运行:
天池 天池是阿里云创建的数据竞赛平台，它和 Kaggle 很像。各个领域的比赛都有，赛制持续时间较长，会...
Can not import feature_engine package's module in Kaggle Editor. (First noting the below lines of codes are working in local machine's Jupyter Notebook, but not in Kaggle ) To Reproduce, I did below inside Kaggle Editor To install feature_engine just the regular code !pip install feature_...
Machine learning. Basic ML is covered in mlcourse.ai. Some Coursera specializations would also be a good entry point. As for Deep Learning, Stanford’s cs231n or fast.ai are two good options. Pet projects and/or competitions. It’s good to show that you’ve done a minimal viable product...