Reduce loss, incress accuracy in sequence! [Machine learning: Deep Learning: Keras: LSTM]

Experienced data scientist who has extensively used LSTM, CNN and other linear, decision tree based algorithms for a variety of projects. Going through the provided information I think that the stated goal can be accomplished. Looking forward to hearing back from you.

I am a professional ML/NLP Engineer in an IT company with 2+ years of Python, Machine learning and Natural Language processing, have experience working with many challenging problems and also with different tools and libraries like Scikit-learn, keras with backend tensorflow, and word2vec, fasttext, textacy etc, let me know if you are interested

Hi I am a very experienced statistician and academic writer. I have completed several PhD level thesis projects involving advanced statistical analysis of data. I have worked with data from several companies and have done projects involving high level quantitative analysis and data interpretation skills to study the trends, time behaviour and compare the variables in the data. I can do advanced level analysis in SPSS, R, PYTHON, WEKA, TABLEAU and EXCEL tools like machine learning, hypothesis testing, forecasting, T-test, ANOVA etc. Looking forward to discussion, Best Regards, Suyash

Hello, I have extensive experience in python and financial markets and would love to help you out on this project. I currently work part-time as a consultant for a long/short equity hedge fund part/time in Palo Alto, CA and have a Masters in financial mathematics/engineering. I think I can be of great help to you. My credentials are below: * Responsible for creating proprietary quantitative models and algorithmic trading strategies for long/short equity optimization models with specific risk and return parameters specified by the investor profile, utilizing machine/deep learning, along with Q reinforcement learning agents. •Created predictive vectorized/event-based machine learning models utilizing multivariate/logistic regression, lasso/ridge regression, linear/quadratic discriminant analysis, decision trees, K neighbors, Naive Bayes, random forest, support vector machine, Adaptiveboost, GradientBoost, XGB, and portfolio optimization to maximize return and minimize volatility for various investor risk profiles. •Responsible for deep learning modeling using recurrent neural networks, Tensorflow, nltk, sentiment analyzer, Keras LSTM, and convolutional neural networks, in attempt to predict specific asset class forecasted prices through stocks, forex, bonds, futures, ETFs, and other derivatives. •Designed a proprietary machine/deep learning long/short intraday algorithm utilizing the Interactive Brokers API, IB_Insync python library. Speak soon!

Since you have invited me to bid yourself, i guess we can discuss the details of the project on chat if you would like to.

I am an expert in Data science, I've done a lot of projects in Machine learning involving data preparation, data visualization, building classifiers and regression model using Python, R and Matlab contact me for further discussion.

hey, I hope you are having a base script for the same. kindly share the same so that I can actually work on what has to be changed to increase the accuracy of your prediction in lstm.