You will get topic modeling in R and Python
Project details
In this project, I offer comprehensive topic modeling services in both R and Python, tailored to your specific needs. With a strong background in data science and natural language processing (NLP), I specialize in extracting meaningful insights from large text datasets.
Types of Topic Modeling:
Latent Dirichlet Allocation (LDA):
A widely used method for discovering topics in a collection of documents by representing each document as a mixture of topics and each topic as a mixture of words.
Non-Negative Matrix Factorization (NMF):
A parts-based representation technique that decomposes the text data into non-negative factors, ideal for producing sparse and interpretable results.
Latent Semantic Analysis (LSA):
Uses singular value decomposition to reduce the dimensionality of text data, capturing the underlying structure and relationships between terms and documents.
Visualization:
Word Clouds: Quickly visualize the most significant terms within topics.
Topic Distributions: Graphically represent how topics are distributed across documents.
Inter-topic Distance Maps: Use t-SNE or UMAP to show the relationships and distances between different topics in a 2D or 3D space.
Types of Topic Modeling:
Latent Dirichlet Allocation (LDA):
A widely used method for discovering topics in a collection of documents by representing each document as a mixture of topics and each topic as a mixture of words.
Non-Negative Matrix Factorization (NMF):
A parts-based representation technique that decomposes the text data into non-negative factors, ideal for producing sparse and interpretable results.
Latent Semantic Analysis (LSA):
Uses singular value decomposition to reduce the dimensionality of text data, capturing the underlying structure and relationships between terms and documents.
Visualization:
Word Clouds: Quickly visualize the most significant terms within topics.
Topic Distributions: Graphically represent how topics are distributed across documents.
Inter-topic Distance Maps: Use t-SNE or UMAP to show the relationships and distances between different topics in a 2D or 3D space.
Machine Learning Tools
NLTK, NumPy, pandas, Python, RWhat's included
| Service Tiers |
Starter
$50
|
Standard
$100
|
Advanced
$200
|
|---|---|---|---|
| Delivery Time | 1 day | 3 days | 3 days |
Number of Revisions | 3 | 5 | Unlimited |
Number of Graphs/Charts | 3 | ||
Model Validation/Testing | - | - | - |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - |
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Eric F.
Feb 7, 2025
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Timely and complete work, I'd absolutely hire him again.
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Will S.
Jan 20, 2025
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Neal F.
Jul 27, 2024
Statistical Analysis Expert Needed
Fantastic work on a short deadline! Mohan was responsive, fast, and did great work. Would definitely use his services again.
EP
Emily P.
Jul 18, 2024
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Cuong T.
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He delivers quickly and makes very few mistakes in the scraped data. If there are any mistakes, they will be fixed within a day. I definitely recommend him if there are multiple milestones in the project!
About Mohan
Data Scientist | Statistician | Data Analyst | R & Python Expert
100%
Job Success
Kathmandu, Nepal - 11:53 pm local time
I am a skilled data analyst with over 10 years of industry experience in collecting, transforming, organizing, and interpreting various types of data sets. My expertise includes, but is not limited to:
Data Analysis & Visualization:
★ Data Cleaning, Aggregation, and Transformation
★ Cross-sectional and Panel Data Analysis
★ Text Mining and Sentiment Analysis
★ Topic Modeling
★ Exploratory Data Analysis
★ Correlation and Regression Analysis
★ ANOVA, ANCOVA, Factor Analysis, Categorical Data Analysis
★ Experimental Design Analysis
★ Time Series Analysis and Forecasting
Machine Learning & AI:
★ Machine Learning Model Development
★ Deep Learning Techniques
★ Large Language Model (LLM) Fine-Tuning
★ Retrieval-Augmented Generation (RAG)
★ Classification and Clustering
★ Recommendation Systems
★ Predictive Modeling
Reporting & Visualization:
★ Report Writing
★ Reproducible Reports with R Markdown
★ Creating Graphs and Charts
★ Animating Graphs and Charts
★ Map Visualization
Web & Data Scraping:
★ Web Scraping
Steps for completing your project
After purchasing the project, send requirements so Mohan can start the project.
Delivery time starts when Mohan receives requirements from you.
Mohan works on your project following the steps below.
Revisions may occur after the delivery date.
Data Collection and Preparation
Gather and preprocess the dataset to ensure it is suitable for topic modeling analysis.
Model Development and Training
Develop and train the topic modeling algorithm using the prepared data, optimizing for accuracy and relevance.