Machine Learning – Anomalies Post

Fundamental and Technical Stock Analysis: A Machine Learning Approach

Abhishek KantherJune 29, 2023June 29, 2023022 mins

Explore the power of machine learning in fundamental and technical stock analysis. Learn how to leverage historical data, financial statements, and predictive modeling techniques to make informed investment decisions. Discover the potential of SARIMAX and AdaBoost algorithms in forecasting stock prices. Gain insights into discount rate calculations, NPV, and IRR to evaluate investment opportunities. Enhance your understanding of stock market trends and improve your trading strategies using this comprehensive guide.

Machine Learning, Dash, and Plotly: Optimizing Stock Portfolios

Abhishek KantherJune 10, 2023February 3, 2024021 mins

Learn how to optimize stock portfolios using machine learning techniques. Discover how to leverage Dash and Plotly libraries to analyze historical stock price data, calculate optimal allocations, and visualize portfolio performance.

Portfolio featured for the period 15th May 2023 to 19th May 2023

Investment Update: Our Weekly Portfolio Strategy for May 15th, 2023

Abhishek KantherMay 13, 2023May 14, 202306 mins

In this article, we analyze a previously suggested portfolio based on BSE SENSEX companies and provide recommendations for a new portfolio for the upcoming week. The article includes a detailed analysis of the performance of the previous portfolios and provides new portfolio recommendations based on Sharpe Ratio and Machine Learning optimization.

Investing in BSE SENSEX Companies for Weekly Returns: Strategies and Tips

Abhishek KantherMay 7, 2023May 7, 202309 mins

Are you a risk-taker or a risk-averse investor? Are you looking for investment advice that can help you make the most out of your stock portfolio while minimizing risks? If so, you might want to consider using Machine Learning (ML) methodologies.

In this article, we will explore how Machine Learning can help you build a profitable investment portfolio on BSE SENSEX companies. We will cover two different portfolios, one that maximizes the Sharpe Ratio and the other that uses ML to perform mean-variance optimization. We will also discuss how cross-validation can be used to choose the best model and achieve better performance.

Market Basket Analysis: A Guide to Finding Hidden Patterns in Customer Purchases

Abhishek KantherFebruary 9, 2023April 17, 2023011 mins

Learn how to use the apriori algorithm and association rules to perform market basket analysis on customer purchase data using Python. Discover hidden patterns in customer purchases and use this knowledge to improve your business strategies.

Data-Backed Strategies for Boosting Your Social Media Reach and Impact featured image

Predicting Stock Price Changes with Python’s Gaussian Naive Bayes Classifier

Abhishek KantherNovember 17, 2022April 17, 2023010 mins

Learn how to use Python’s Gaussian Naive Bayes classifier to predict changes in stock prices. Our step-by-step guide will help you analyze historical stock data and train a model to make accurate predictions.

Understanding CatBoost Algorithm of LIVE Stock Data: A Comprehensive Guide Using PYTHON

Abhishek KantherOctober 11, 2022April 17, 2023020 mins

CatBoost is a powerful gradient boosting algorithm that has gained popularity in the field of machine learning due to its ability to handle categorical data and produce accurate predictions. This article provides a comprehensive guide on CatBoost, covering its features, advantages, and implementation in Python.

Mastering Stock Price Prediction with LSTM Model in Python

Abhishek KantherSeptember 2, 2022April 17, 2023017 mins

Learn how to predict stock prices with the powerful LSTM model in Python. This article covers step-by-step instructions and code examples to help you become a stock price prediction expert.

Predicting Stock Prices with AdaBoost Algorithm: A Comprehensive Guide Using Python

Abhishek KantherAugust 2, 2022April 17, 202308 mins

Learn how to use the AdaBoost Algorithm to forecast stock prices accurately in python. Our step-by-step guide includes code examples, explanations of key concepts, and tips for improving the accuracy of your predictions.

Using Random Forest Algorithm for High-Dimensional Datasets with Complex Interactions in Python

Abhishek KantherJuly 6, 2022April 18, 202306 mins

In this article, we explore how the random forest algorithm can be used for datasets with high dimensions and complex feature interactions. We provide sample code in Python for generating such a dataset and running a random forest regression model. We also analyze the model’s feature importances and provide a summary of the results.

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Tag: Machine Learning

Fundamental and Technical Stock Analysis: A Machine Learning Approach

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Machine Learning, Dash, and Plotly: Optimizing Stock Portfolios

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Investment Update: Our Weekly Portfolio Strategy for May 15th, 2023

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Investing in BSE SENSEX Companies for Weekly Returns: Strategies and Tips

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Market Basket Analysis: A Guide to Finding Hidden Patterns in Customer Purchases

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Predicting Stock Price Changes with Python’s Gaussian Naive Bayes Classifier

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Understanding CatBoost Algorithm of LIVE Stock Data: A Comprehensive Guide Using PYTHON

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Mastering Stock Price Prediction with LSTM Model in Python

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Predicting Stock Prices with AdaBoost Algorithm: A Comprehensive Guide Using Python

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Using Random Forest Algorithm for High-Dimensional Datasets with Complex Interactions in Python

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