Fit noisy data to polynomial in IPython notebook

I read your project description carefully. I am bidding on your project becasue I am very much familiar with All the NN topics mentioned above and did lot of project in jupyter notebook. I am an experienced Data Scientist and Machine Learning Engineer. Data Visualization, NLP, Deep learning, Artificial intelligence, machine learning, Data structures, and algorithms are my major fields. I finished specializations on Data Science, Machine learning, Deep neural Network, Convolution NN, Recurrent NN, Tuning Hyper Parameter .this project will well fit for me. I have won the 2nd runners up award in Sri Lanka Biggest Data Science Competition. I am very fluent with python and did a lot of data science and ml project. So I am familiar with these related libraries such as matplotlib, seaborn, pandas, numpy, sikit-learn, Keras, TensorFlow, spark etc .

Hello There, I am a Data Scientist with 2+yrs of experience and would love to work for you on this project. Lets discuss the details and get started.

Hi, I have experience with various polynomial fitting algorithms used in ML. I also have use Jupyter's Ipython notebook. If interested please provide details via chat.

Hi There, A bit tweaking with co-efficients and some other techniques can do the trick and then noisy data can easily fit to polynomial. I am IBM Certified Data Science Professional and I am working in Jupyter Notebook for the last 2 years. Let's connect and get your noisy data fitted to polynomial Thank You

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