Update README.md

Author: Archi20876

Data Analysis/Sentiment Analysis - Dow Jones (DJIA) Stock using News Headlines/README.md

@@ -14,22 +14,30 @@ This project focuses on sentiment analysis, a technique used to determine the em
 
 ### Approach :
 - Data Cleaning & Preprocessing: Clean the data to remove noise (e.g., hashtags, URLs, special characters), and preprocess it by tokenizing, removing stopwords, and lemmatizing the text.
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 - Exploratory Data Analysis (EDA):
 Visualize the distribution of sentiments in the dataset.
 Identify common words and phrases associated with positive and negative sentiments.
 Analyze sentiment over time to observe trends.
-  Model Development: Use machine learning algorithms such as Naive Bayes, Multinomial Naive Bayes,Random Forest Classifier , Logistics Regression or deep learning techniques like LSTM to build a sentiment classification model.
-- Sentiment Scoring: Assign sentiment scores to text to quantify the degree of positivity or negativity. 
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+ - Model Development: Use machine learning algorithms such as Naive Bayes, Multinomial Naive Bayes,Random Forest Classifier , Logistics Regression or deep learning techniques like LSTM to build a sentiment classification model.
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+- Sentiment Scoring: Assign sentiment scores to text to quantify the degree of positivity or negativity.
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 - Evaluation & Optimization: Evaluate model performance with precision metrics.
 
 ### Applications :
 
 Businesses: Use predictive insights to improve products, services, and customer engagement strategies.
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 Marketing Teams: Forecast the success of campaigns and adjust strategies based on predicted trends.
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 Social Media Monitoring: Track real-time sentiment and predict future public reactions to events, products, or announcements.
 
-To view the Analysis 👉 [Sentiment Analysis.ipynb](https://github.com/Archi20876/machine-learning-repos/blob/main/Data%20Analysis/Sentiment%20Analysis%20-%20Dow%20Jones%20(DJIA)%20Stock%20using%20News%20Headlines/Stock%20Sentiment%20Analysis.ipynb)
 
-To view More charts in the Analysis 👉 [Sentiment analysis charts](https://github.com/Archi20876/machine-learning-repos/blob/main/Data%20Analysis/Sentiment%20Analysis%20-%20Dow%20Jones%20(DJIA)%20Stock%20using%20News%20Headlines/ChartsForBetterUnderstanding.ipynb)
 
-To view the Dataset 👉 [Dataset](https://github.com/Archi20876/machine-learning-repos/blob/main/Data%20Analysis/Sentiment%20Analysis%20-%20Dow%20Jones%20(DJIA)%20Stock%20using%20News%20Headlines/Stock%20Headlines.csv)
+## To view the Analysis 👉 [Sentiment Analysis.ipynb](https://github.com/Archi20876/machine-learning-repos/blob/main/Data%20Analysis/Sentiment%20Analysis%20-%20Dow%20Jones%20(DJIA)%20Stock%20using%20News%20Headlines/Stock%20Sentiment%20Analysis.ipynb)
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+## To view More charts in the Analysis 👉 [Sentiment analysis charts](https://github.com/Archi20876/machine-learning-repos/blob/main/Data%20Analysis/Sentiment%20Analysis%20-%20Dow%20Jones%20(DJIA)%20Stock%20using%20News%20Headlines/ChartsForBetterUnderstanding.ipynb)
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+## To view the Dataset 👉 [Dataset](https://github.com/Archi20876/machine-learning-repos/blob/main/Data%20Analysis/Sentiment%20Analysis%20-%20Dow%20Jones%20(DJIA)%20Stock%20using%20News%20Headlines/Stock%20Headlines.csv)