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Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

  • Updated Nov 4, 2021
  • Python
datasets
mariosasko
mariosasko commented Nov 12, 2021

f-strings offer better readability/performance than str.format and %, so we should use them in all places in our codebase unless there is good reason to keep the older syntax.

NOTE FOR CONTRIBUTORS: To avoid large PRs and possible merge conflicts, do 1-3 modules per PR. Also, feel free to ignore the files located under datasets/*.

Data-Science-For-Beginners

人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理,PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

  • Updated Feb 6, 2020
martin3000
martin3000 commented Aug 26, 2021

Reading currencies, alphavantage returns a greeting note ("welcome") and this note raises an error in alphavantage.py line 363.

            elif "Note" in json_response and self.treat_info_as_error:
                raise ValueError(json_response["Note"])

For this reason, alphavantage does not work in home assistant.

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

  • Updated Nov 10, 2021
  • Python

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