You will get I will build machine learning models with clean data preprocessing
Project details
I will develop a complete machine learning solution tailored to your dataset and requirements. This includes data cleaning, preprocessing, feature engineering, model building, hyperparameter tuning, evaluation metrics, and a fully documented Python codebase.
What I offer:
Data cleaning and preprocessing (missing values, outliers, encoding, scaling)
Exploratory data analysis (EDA)
ML model development (classification, regression, clustering)
Deep learning models using TensorFlow or PyTorch
NLP pipelines using NLTK, BERT, SBERT, Transformers
Optimization & evaluation
Deployment-ready scripts (Streamlit/Gradio optional)
Clear explanations + documentation
I ensure a clean, accurate, and efficient ML pipeline suitable for production, research, or academic use. You will receive the complete code, results, and support at every step.
What I offer:
Data cleaning and preprocessing (missing values, outliers, encoding, scaling)
Exploratory data analysis (EDA)
ML model development (classification, regression, clustering)
Deep learning models using TensorFlow or PyTorch
NLP pipelines using NLTK, BERT, SBERT, Transformers
Optimization & evaluation
Deployment-ready scripts (Streamlit/Gradio optional)
Clear explanations + documentation
I ensure a clean, accurate, and efficient ML pipeline suitable for production, research, or academic use. You will receive the complete code, results, and support at every step.
Machine Learning Tools
BERT, ChatGPT, GPT-3, Keras, NLTK, NumPy, pandas, Python, Python Scikit-Learn, PyTorch, SQL, TensorFlowWhat's included
| Service Tiers |
Starter
$5
|
Standard
$7
|
Advanced
$10
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 2 |
Number of Graphs/Charts | 1 | 2 | 3 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
About Swathi
Entry-Level Machine Learning Engineer | Data Analyst
Amalapuram, India - 5:05 am local time
Iam a Machine Learning & AI Engineer with hands-on experience building real, production-ready AI solutions using Python, Deep Learning, NLP, Transformers, and LLM-based pipelines. I specialize in creating intelligent systems that turn raw data into accurate predictions, insights, and automation.
My work includes building end-to-end ML applications, optimizing deep learning models, creating semantic search & embedding-based systems, and deploying user-friendly AI tools using Streamlit, Gradio, and HuggingFace Spaces.
What I Can Build for You:
Custom Machine Learning models (classification, prediction, clustering, optimization)
NLP solutions (resume parsing, semantic search, text extraction, summarization)
LLM-based pipelines using Transformers, Sentence-BERT, RAG, FAISS
Deep learning models (CNNs, image classification, benchmarking)
AI-powered dashboards & web apps (Streamlit/Gradio)
Automations using Python, APIs, and data workflows
Complete end-to-end AI product development
Key Highlights:
Improved deep learning model performance by 60% and reduced inference latency by 62%
Built HireMatch-AI, a semantic resume-job matching platform using embeddings
Built & deployed projects on HuggingFace Spaces with live demos
Experienced with TensorFlow, Keras, Scikit-learn, Transformers, NumPy, Pandas, Plotly
I’m detail-oriented, fast-learning, and committed to delivering clean, reliable, and scalable AI solutions. Whether you need a small script, a custom model, or a complete AI workflow — I can help you build it efficiently.
Let’s work together to bring your AI idea to life!
Steps for completing your project
After purchasing the project, send requirements so Swathi can start the project.
Delivery time starts when Swathi receives requirements from you.
Swathi works on your project following the steps below.
Revisions may occur after the delivery date.
Review client requirements and dataset
I review the dataset, understand the project goal, and confirm the approach.
Perform data cleaning and preprocessing
I clean the dataset (missing values, duplicates, formatting, encoding, scaling).