You will get high accuracy audio classification work done.
Tanisha B.
You will get high accuracy audio classification work done.
Tanisha B.
Project details
You will get high accuracy audio classification python notebook file and Machine Learning model. The code will be documented.
$100
- Delivery Time 5 days
- Number of Revisions 1
- Model Validation/Testing
- Model Documentation
- Source Code
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KO
Kenneth O.
May 22, 2023
PDF Data scraper
She was very transparent and ready to work. Will recommend her for future jobs
AL
Adam L.
Oct 27, 2021
[HIGH PAY]: Seeking Machine Learning/Python Programmer for Very Short/Rapid Federated Learning Task
Tanisha was superb! One of the best programmers I have worked with — we are a large company based out of New York City that really needed a freelancer to test our software and help solve bugs/implement functions, and she did in under 48 hours with perfection and ease of a professional. Would highly recommend working with Tanisha should you have the opportunity!
EA
Evi A.
Oct 9, 2021
You will get high accuracy audio classification work done.
SB
Swapnil B.
Jun 12, 2021
Padas df list and defaultdict() matching two dictionary
SB
Swapnil B.
May 20, 2021
Pandas df compare
Best developer to work..... Fast
About Tanisha
Full Stack AI Engineer || AI Researcher and Developer
50%
Job Success
Ahmedabad, India - 7:59 pm local time
* I develop end-to-end AI systems from requirements analysis, data gathering to deployment, implementing new methods/research papers, turning projects into research outcomes. Achieved substantial performance in DL/ML models for CV and NLP domain problems.
* Implementing and deploying projects, research papers as well as POCs.
* Project planning, requirements gathering, analysing requirements to define the architecture of the system, and timeline to implement them.
• Machine Learning and Data Visualization: tensorflow, PyTorch, scikit-learn, keras, NumPy, Pandas,
seaborn, matplotlib
• Programming Methodologies: OOPS, Functional
• Machine Learning Deployment: Docker, Kubernetes
• Databases and Languages: Python, C, C++, JavaScript, MySQL, PostgreSQL, MongoDB
• Software and Frameworks: Flask, Angular, Jupyter, GitHub, git
Summary:
I like to work on technology that is smart, simple and sophisticated. These sums up the vast amount of knowledge required to work on projects to excel it into a working product. I like to train Deep Neural Networks, and understand them well.
I have mentored many students for their career in AI, taught them Machine Learning and Mathematics. Currently, I am a mentor for the RFS (Reach for the Stars) Programme by Aga Khan Education Board for India. I am an alumnus of this program as well.
I have a cumulative experience of 6 years working in the product and service-based industry for creating Machine Learning projects.
I have done some innovative work that I am proud of and am continuing to do so. I try my best to contribute my expertise to the project I am working in.
Machine Learning, Deep Learning, Advanced Deep Learning, Artificial Intelligence, Algorithms, including models in the production environment, deploying ML models.
I have 6 years of experience and have successfully deployed models in the following domains of Deep Learning:
Computer Vision:
# CNN
# MaskRCNN
# Object Detection
# Object Recognition
# Image Classification
# Clustering and Annotation
# Image Segmentation
# Medical Image Analysis
# Automatic Segmentation
Generative Models
# Generative Adversarial Networks
# Hidden Markov Models
# Bayes Method
Representation Learning:
# Autoencoders
# Variational Autoencoders
# Word Embeddings
# Image Embeddings
# Manifold Learning
Federated Learning:
# Adversarial Attacks in Federated Learning setting
# Combating Adversarial Attacks in Federated Learning
# Implementing Federating Learning algorithms
NLP:
# Word2Vec
# GloVe
# BERT (and its variants)
# GPT (DistilGPT)
# LSTM, GRU, RNN (CNN + RNN)
# Implementing and fine-tuning the above models.
# Creating custom Deep Learning models for the custom use-case
# OpenAI API, langchain, Llama.
# Running LLMs on a custom server (keeping your data private)
# Prompt Engineering
Audio Models:
# MFCC representation and classification
Steps for completing your project
After purchasing the project, send requirements so Tanisha can start the project.
Delivery time starts when Tanisha receives requirements from you.
Tanisha works on your project following the steps below.
Revisions may occur after the delivery date.
Data Validation step
Check whether the data provided is correct or not.
Model creation and code completion
Create model on the correct dataset