You will get An AI-powered application for automation, analysis, or text intelligence
Project details
I will build an AI-powered application using Python, NLP, and modern LLM workflows for automation, analysis, and intelligent user experiences.
Possible solutions include:
• Resume screening tools
• AI-powered dashboards
• Document analysis
• Semantic search systems
• Text classification
• Chatbots and AI assistants
• Embedding and retrieval workflows
Features can include:
• File upload support
• Interactive dashboards
• AI-generated insights
• Search and recommendation systems
• Streamlit-based interfaces
Technologies:
Python • NLP • Streamlit • OpenAI APIs • Embeddings • Scikit-learn
Ideal for startups, business automation, and rapid AI prototyping.
Possible solutions include:
• Resume screening tools
• AI-powered dashboards
• Document analysis
• Semantic search systems
• Text classification
• Chatbots and AI assistants
• Embedding and retrieval workflows
Features can include:
• File upload support
• Interactive dashboards
• AI-generated insights
• Search and recommendation systems
• Streamlit-based interfaces
Technologies:
Python • NLP • Streamlit • OpenAI APIs • Embeddings • Scikit-learn
Ideal for startups, business automation, and rapid AI prototyping.
AI Algorithms
CycleGAN, Feedforward Neural Network, Large Language Model, Linear Discriminant Analysis, Multilayer Perceptron, Multimodal Large Language Model, Regression Analysis, StyleGAN, Transformer Model, YOLOAI Applications
AI Chatbot, AI-Enhanced Classification, AIOps, Anomaly Detection, Conversational AI, Natural Language Understanding, Object Detection, Sentiment Analysis, Sequence Modeling, Time Series Analysis, Time Series ForecastingAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Gradio, Hugging Face, NVIDIA AI Platform, PyTorch, Replit, Streamlit, TensorFlow, Word2vecAI Models
BERT, ChatGPT, LLaMA, Naive Bayes Classifier, OpenAI Codex, Stable DiffusionWhat's included
| Service Tiers |
Starter
$60
|
Standard
$140
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 7 days |
Number of Revisions | 2 | 3 | 5 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | ||
Detailed Code Comments | |||
Image Upscaling | - | - | - |
MLOps | - | - | |
Model Deployment | - | - | |
Model Documentation | - | - | |
Model Monitoring | - | - | |
Model Testing & Optimization | - | ||
Model Tuning | - | ||
Natural Language Processing | - | ||
NLP Tokenization | - | ||
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | |||
Source Code |
About Shubham
Data Scientist | Python, SQL, ML, Dashboards & Automation Expert
Thane, India - 8:02 pm local time
I help businesses turn messy data into actionable insights using Python, SQL, machine learning, and interactive dashboards.
I have experience building:
• Predictive ML models
• Automated ETL pipelines
• Streamlit dashboards
• Recommendation systems
• Analytics workflows using Python, SQL, Spark, and cloud tools
Previously, I worked on:
• Student performance prediction systems
• Recommendation engines
• Real-time analytics dashboards
• ML pipelines with experiment tracking
• Forecasting and anomaly detection projects
Tools & Technologies:
Python • SQL • Pandas • Scikit-Learn • XGBoost • Streamlit • Tableau • Power BI • Spark • AWS • PostgreSQL
I focus on fast communication, clean code, and practical business solutions.
Steps for completing your project
After purchasing the project, send requirements so Shubham can start the project.
Delivery time starts when Shubham receives requirements from you.
Shubham works on your project following the steps below.
Revisions may occur after the delivery date.
Use Case & Workflow Planning
Understand the AI workflow, user requirements, datasets, and expected functionality.
AI & NLP Development
Build AI workflows including NLP, embeddings, prompt engineering, or automation.