analytics
Browse files- app.py +13 -12
- requirements.txt +2 -1
app.py
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@@ -194,15 +194,17 @@ With no need for jargon, SSDS delivers tangible value to our fintech operations.
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gr.Markdown("""
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=========
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By identifying growth and decline industries, traders can make informed investment decisions and speed up trading by investing in companies that are likely to experience growth in the future and avoiding companies that are likely to experience a decline in the future.
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""")
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with gr.Tab("Trading Analyics"):
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in_ts = gr.Textbox(placeholder="QQQM CIF VEGI PJP",
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btn_ts.click(fn=trend, inputs=in_ts, outputs=plot)
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gr.Markdown("""
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=========
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Our aim is to extract meaningful insights from customer interactions to improve our services, products, and overall customer experience. This analysis will help us understand what our customers are discussing and how they feel about different aspects of our business.
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- intervene attrition through incentive
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""")
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demo.launch()
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[in_like]
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gr.Markdown("""
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Smart Insights: Elevating Customer Engagement Through Sentiment Analysis
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As a Data Scientist with a decades of financial industry experience, I recognize the paramount importance of staying closely tuned to our customer's needs and opinions. In this app, Fine Tune LLM, we have shown how fine-tuning a Language Model (LLM) on a custom dataset can provide valuable insights into customer sentiment across crucial areas such as service, sales, point of failure, product, and emerging trends.
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Objective:
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Our aim is to extract meaningful insights from customer interactions to improve our services, products, and overall customer experience. This analysis will help us understand what our customers are discussing and how they feel about different aspects of our business.
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Use Case:
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- intervene attrition through incentive
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""")
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with gr.Tab("Trading Analyics"):
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in_ts = gr.Textbox(placeholder="QQQM CIF VEGI PJP",
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btn_ts.click(fn=trend, inputs=in_ts, outputs=plot)
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gr.Markdown("""
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Maximizing Trading Efficiency: Personalize Your Asset Allocation for Optimal Growth
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The industry life cycle is a useful tool for traders to identify growth and decline industries. It describes the evolution of an industry based on its stages of growth and decline 1. There are four phases of the industry life cycle: introduction, growth, maturity, and decline 2.
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A growth industry is a sector of an economy that experiences a higher-than-average growth rate compared to other sectors. Growth industries are often new or pioneer industries that did not exist in the past. Their growth is a result of demand for new products or services offered by companies in the field 3. Identifying growth industries can help traders to speed up trading by investing in companies that are likely to experience rapid growth in the future.
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On the other hand, a decline industry is a sector of an economy that is experiencing a lower-than-average growth rate compared to other sectors. Identifying decline industries can help traders to avoid investing in companies that are likely to experience a decline in the future 2. This can help traders to minimize losses and maximize profits.
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By identifying growth and decline industries, traders can make informed investment decisions and speed up trading by investing in companies that are likely to experience growth in the future and avoiding companies that are likely to experience a decline in the future.
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""")
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demo.launch()
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requirements.txt
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chromadb
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fastai
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yfinance
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scikit-learn
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seaborn
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chromadb
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fastai
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yfinance==0.2.31
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pandas==2.1.3
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scikit-learn
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seaborn
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