Machine Learning Bot

Machine Learning Bot

224
Views

Machine Learning Bots|$400 Python Optimize Finance Time Series A.I. Python Deep/Machine Learning Bots/Backtest|4 Days Delivery

Marketplacenairobitravelcraig posted the article • 0 comments • 224 views • 2021-02-08 21:34 • data from similar tags

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.


 

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.

 

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. 

 

Proprietary machine/deep learning long/short intraday algorithm utilizing the Interactive Brokers API, IB_Insync python library. view all
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.


 

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.

 

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. 

 

Proprietary machine/deep learning long/short intraday algorithm utilizing the Interactive Brokers API, IB_Insync python library.
224
Views

Machine Learning Bots|$400 Python Optimize Finance Time Series A.I. Python Deep/Machine Learning Bots/Backtest|4 Days Delivery

Marketplacenairobitravelcraig posted the article • 0 comments • 224 views • 2021-02-08 21:34 • data from similar tags

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.


 

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.

 

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. 

 

Proprietary machine/deep learning long/short intraday algorithm utilizing the Interactive Brokers API, IB_Insync python library. view all
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.


 

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.

 

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. 

 

Proprietary machine/deep learning long/short intraday algorithm utilizing the Interactive Brokers API, IB_Insync python library.