analyzing temperature data in aws.

Hi there,I'm biddin on your project "analyzing temperature data in aws." I have read your project description and i'm an expert in Python and machine learning therefore i can do this project for you perfectly.I still have a few questions. please leave a message on my chat so we can discuss the budget and deadline of the project. Thanks. .. .

Hi, I am an experienced Data Engineer with a solid background in AWS. I can do analysis in quicksight or kinesis Data Analytics. Let's have a call for more details about the project. Regards

Hi there, I am a talented python dev, and I suppose I can handle this task successfully. Please let me know more details, and Please give me your chance. I look forward to hearing from you. Regards!

Hi! I did this project before. I am sending temp and humidity data from my DTH22 sensor to AWS IoT Core. From IoT Core, it can send data to IoT Analytics like AWS quicksite to create dashboards. IoT rules can be setup if you want to be notified if value reach some set threshold. I would like to know if you just want to visualize data or more. Regards Maqsud

YOUR BID Hello, how are you? I know how to analyzing temperature data in aws I hope we can discuss more about detail. Since this is my first time to take project here, I will charge less and do it more seriously, to get recognition and good comment, Hope I can have this opportunity! Looking forward hearing from you! Here is my profile. 3 year experience for Python development - Use Python for function and algorithm development, service construction, etc; familiar with C/C++ and java for development. - Proficient in using Linux operating system, git, docker and other tools; - Familiar with KMP, Trie, AC automaton, simhash, Harris corner detection, sift and other algorithms; - Use numpy, pandas, sklearn and other scientific computing or machine learning algorithm libraries, including data preprocessing, regression, classification, clustering and other model selection, feature selection, feature reduction, cross-validation, model evaluation and other basic machine learning algorithm modules ; - Familiar with the basic principles of machine learning algorithms, such as logistic regression, SVM, clustering algorithm, K-means, KNN, decision tree, naive Bayes, HMM, CRF, EM algorithm, XGBoost, etc. - Basic theory of deep learning, CNN, RNN and other model principles; LSTM, Transformer, Inception, Resnet, RCNN, YOLO and other model structures. - Skilled use of mysql, mongodb type database; - Familiar with tensorflow/Pytorch and other frameworks;