reiserbc

AI-Assistant

An assistant that can automate the process of clicking screenshots, saving data to file, reading data from the file, wiki search, can logout, shutdown, restart the pc, give you details about cpu usage and battery updates, can play songs, can joke, greet you according to the time of the day, can tell you current date and time, perform google search, can send an email. All of this on voice control and voice recognition

alpha

ArduinoBipedalWalkingRobot_NeuralNetwork

Bipedal_robot

BEARR The Bipedal Electronic Autonomous Radical Robot. Fully self walking robot built by Max Leblang and Elijah Tolten.

Blinky

Eye tracking & virtual keyboard application to improve communication for disabled people.

cnn-lstm-stock

CNN-LSTM stock prediction algorithm project

Deep-Learning-Machine-Learning-Stock

Stock for Deep Learning and Machine Learning

Eye-blink-to-speech

Motor Neuron Disease (MND) is a medical condition where the motor neurons of the patient are paralyzed, it is incurable. It also leads to weakness of muscles with respect to hand, feet or voice. Because of this, the patient cannot perform his voluntary actions and it is very difficult for the patient to express his needs as he is not able to communicate with the world. There are many methods introduced for the motor neuron disease patients to communicate with the outside world such as Brain wave technique and Electro-oculography. Loss of speech can be hard to adjust. It is difficult for the patients to make the caretaker understand what they need especially when they are in hospitals. It becomes difficult for the patients to express their feelings and even they cannot take part in conversations. System incorporates different visual technologies, such as eye blink detection, eye centre localization and conversion of the eye blink to speech. The proposed system detects the eye blink and differentiates between an intentional long blink and a normal eye blink. The proposed system can be used to control and Communicate with other people. The objectives of the system are: Capturing the frame from the video using the system’s camera initialises the execution of the proposed system.The Face Detection Algorithm then processes on the captured video frames to give out the rectangular boxed face. This output from Face Detection Algorithm then gets processed using AdaBoost Classifier to detect the eye region in the face.Eye detected will be sent to check if there is any movement of the eyeball. If it’s there, then this movement will be tracked to give out the combination the patient is using to express the dialogue.If not, then the blink pattern will be processed to give out the voice as well as the text input with respective dialogue.

EZ-Robot-With-Cognitive-Services

This repo contains sample application for EZ Robot JD Humanoid which adds cognitive abilities to robot using selected Microsoft Cognitive Services

FinancialVision

FinancialVision

reiserbc/alpha

reiserbc/Bipedal_robot

BEARR The Bipedal Electronic Autonomous Radical Robot. Fully self walking robot built by Max Leblang and Elijah Tolten.

reiserbc/cnn-lstm-stock

CNN-LSTM stock prediction algorithm project

reiserbc/Deep-Learning-Machine-Learning-Stock

Stock for Deep Learning and Machine Learning

reiserbc/Eye-blink-to-speech

Motor Neuron Disease (MND) is a medical condition where the motor neurons of the patient are paralyzed, it is incurable. It also leads to weakness of muscles with respect to hand, feet or voice. Because of this, the patient cannot perform his voluntary actions and it is very difficult for the patient to express his needs as he is not able to communicate with the world. There are many methods introduced for the motor neuron disease patients to communicate with the outside world such as Brain wave technique and Electro-oculography. Loss of speech can be hard to adjust. It is difficult for the patients to make the caretaker understand what they need especially when they are in hospitals. It becomes difficult for the patients to express their feelings and even they cannot take part in conversations. System incorporates different visual technologies, such as eye blink detection, eye centre localization and conversion of the eye blink to speech. The proposed system detects the eye blink and differentiates between an intentional long blink and a normal eye blink. The proposed system can be used to control and Communicate with other people. The objectives of the system are: Capturing the frame from the video using the system’s camera initialises the execution of the proposed system.The Face Detection Algorithm then processes on the captured video frames to give out the rectangular boxed face. This output from Face Detection Algorithm then gets processed using AdaBoost Classifier to detect the eye region in the face.Eye detected will be sent to check if there is any movement of the eyeball. If it’s there, then this movement will be tracked to give out the combination the patient is using to express the dialogue.If not, then the blink pattern will be processed to give out the voice as well as the text input with respective dialogue.

reiserbc/FinancialVision

FinancialVision

reiserbc/Forex_Price_Movement

FOREX Trend Classification using Machine Learning Techniques.

reiserbc/forex_rl

Automated trading system for foreign exchange trading using Deep Q-Learning with a deep neural network (CNN) and some intelligent trading strategies

reiserbc/LSTM---Stock-prediction

A long term short term memory recurrent neural network to predict forex data time series

reiserbc/Machine_Learning_trading

implement several Machine Learning algorithms to automate forex trading

reiserbc/MachineLearningStocks

Using python and scikit-learn to make stock predictions

reiserbc/ML-StockAnalysisProject

Modular Analysis of Stock Patterns using Machine Learning Techniques

reiserbc/NeuroEvolutionMarketTrader

Neuro evolution agent to buy and sell stocks atumatically

reiserbc/projetoELA

Eye Tracker for improving communication with Amyotrophic Lateral Sclerosis carriers.

reiserbc/rasa

💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants

reiserbc/Real-time-stock-market-prediction

In this repository, I have developed the entire server-side principal architecture for real-time stock market prediction with Machine Learning. I have used Tensorflow.js for constructing ml model architecture, and Kafka for real-time data streaming and pipelining.

reiserbc/Real-Time-Voice-Cloning

Clone a voice in 5 seconds to generate arbitrary speech in real-time

reiserbc/resemble-unity-text-to-speech

Resemble's voice cloning engine within Unity

reiserbc/ScalpingAlgoTrader

An automated stock trading strategy.

reiserbc/stock-market-prediction

A detailed study of four machine learning Techniques(Random-Forest, Linear Regression, Neural-Networks, Technical Indicators(Ex: RSI)) has been carried out for Google Stock Market prediction using Yahoo and Google finance historical data.

reiserbc/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

reiserbc/Stock-Prediction-Models

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

reiserbc/Stock-Price-Prediction

Predicted the closing stock price of Apple Inc. using an artificial recurrent neural network called Long Short Term Memory (LSTM) with the past 60 days of stock price

reiserbc/Stock-Price-Prediction-Machine-Learning

This is 6th and last capstone project in the arrangement of the undertakings recorded in Udacity-Machine Learning Nano Degree Program. Venture firms, mutual funds and even people have been utilizing monetary models to more readily comprehend market conduct and make beneficial speculations and exchanges. An abundance of data is accessible as chronicled stock costs and friends execution information, reasonable for AI calculations to measure. Could we really foresee stock costs with AI? Financial backers make instructed surmises by dissecting information. They'll peruse the news, study the organization history, industry patterns and different bunches of information focuses that go into making a forecast. The common speculations is that stock costs are absolutely arbitrary and unusual yet that brings up the issue why top firms like Morgan Stanley and Citigroup enlist quantitative examiners to fabricate prescient models. We have this thought of an exchanging floor being loaded up with adrenaline implant men with free ties going around hollering something into a telephone however nowadays they're bound to see columns of AI specialists unobtrusively sitting before PC screens. Truth be told about 70% of all orders on Wall Street are currently positioned by programming, we're presently living in the age of the calculation. This venture uses Deep Learning models, Long-Short Term Memory (LSTM) Neural Network calculation, to anticipate stock costs. For information with time periods intermittent neural organizations (RNNs) prove to be useful however late explores have shown that LSTM, networks are the most famous and valuable variations of RNNs. I have utilized Keras to assemble a LSTM to foresee stock costs utilizing chronicled shutting cost and exchanging volume and envision both the anticipated value esteems after some time and the ideal boundaries for the model.

reiserbc/stock-trading-ml

A stock trading bot that uses machine learning to make price predictions.

reiserbc/stockDL

A financial deep learning library for stocks price prediction and comparison with traditional investment strategies. The Library is based on LSTM-Neural Networks and Conv1D + LSTM Neural Networks. Investments are subject to market risks, The AUTHOR HOLDS NO RESPONSIBILITY for any financial loss.

reiserbc/StockMarketPrediction

An attempt to use RNN (Recurrent Neural Networks) to predict market opening values using TensorFlow and Keras.

reiserbc/StockTrader

Reinforcement Learning applied to the stock market

reiserbc/tradingview-scripts

tradingview pinescripts

reiserbc/TradingView_Machine_Learning

Let Python optimize the best stop loss and take profits for your TradingView strategy.