Platforms Design of Real-Time Stock Market Trading

About the Webinar

Stock market prediction and analysis are some of the most difficult jobs to complete. There are numerous causes for this, including market volatility and a variety of other dependent and independent variables that influence the value of a certain stock in the market. These variables make it extremely difficult for any stock market expert to anticipate the rise and fall of the market with great precision. In this webinar you will learn to Source your dataset, clean it and apply various machine learning algorithms to perform Stock Market Prediction.

What You Will Learn in the Workshop?

• Performing Missing Value Identification and Data Cleaning
• Identify Important Factors for Stock Value Prediction
• Implementing ML Algorithm to predict future trends of Stock Value
• Performing analysis on result to verify model accuracy

About the Trainer

Mr Aayush Kubba is an AI and data science professional with strong business acumen and 10 years of technical experience. He is developing a conversational AI platform for Indian languages (multi lingual architecture) utilizing automatic speech recognition, speech generation and intent engine to power Speech Analytics, Voice-bots and discover business insights. He has experience in DS, AI, ML along with toolkit such as Python (Numpy, Scikit-Learn, Keras, Scikit-Surprise, XGBoost, Tensor flow) and a good working knowledge of various machine learning models like Decision Trees, Random forest, Bagging, Boosting, Naïve Bayes, KNN, Logistic Regression, Linear/Polynomial Regression, Neural Networks, Clustering(K-Means), GBM, Deep Learning, Time Series Forecasting.