You will get nlp and text analysis projects using ml,dl and tensorflow
Project details
Hey! If you are looking for a gig that can provide you with NLP and ML tasks coded professionally using Python, then yes you come to the right place.
Experience in NLP techniques such as:
Tokenization
Text Similarity
Text Cleaning
Vectorization
N-gram Analysis
Lemmatization
Stemming
Information Retrieval
Handling Categorical Data
Feature Engineering
Sentiment Analysis
word/sentence tokenization,
parts of speech tagging,
spelling correction,
removal (stopwords, punctuation, urls, tags, numerals),
stemming,
Word Embeddings
TFIDF
GloVe
Word2Vec
Sentence Embeddings
Sentiment analysis
answer question systems
topic modelling
clustering
sentence similarity
text/document summarization
name entity recognition
text generation
text classification and keyword extraction are just a few of the techniques used.
Support Vector Machine
Nearest Neighbors
Naive Bayes
Decision Trees etc. are ML algorithms.
DL algorithms, including MLPs, CNNs, LSTMs, and RNNs.
BERT, T5, GPT, and other transformers
Platform:
Jupyter Notebook
Google Colab, Pycharm
Tools I use in Python for Project:
Pandas
Numpy
Regular Expression
NLTK
Spacy
Seaborn, Matplotlib, Plotly
Neattext
Scikit-learn, Keras, TensorFlow
Experience in NLP techniques such as:
Tokenization
Text Similarity
Text Cleaning
Vectorization
N-gram Analysis
Lemmatization
Stemming
Information Retrieval
Handling Categorical Data
Feature Engineering
Sentiment Analysis
word/sentence tokenization,
parts of speech tagging,
spelling correction,
removal (stopwords, punctuation, urls, tags, numerals),
stemming,
Word Embeddings
TFIDF
GloVe
Word2Vec
Sentence Embeddings
Sentiment analysis
answer question systems
topic modelling
clustering
sentence similarity
text/document summarization
name entity recognition
text generation
text classification and keyword extraction are just a few of the techniques used.
Support Vector Machine
Nearest Neighbors
Naive Bayes
Decision Trees etc. are ML algorithms.
DL algorithms, including MLPs, CNNs, LSTMs, and RNNs.
BERT, T5, GPT, and other transformers
Platform:
Jupyter Notebook
Google Colab, Pycharm
Tools I use in Python for Project:
Pandas
Numpy
Regular Expression
NLTK
Spacy
Seaborn, Matplotlib, Plotly
Neattext
Scikit-learn, Keras, TensorFlow
Machine Learning Tools
BERT, Deeplearning4j, fastText, Google Sheets, Keras, Microsoft Excel, Microsoft Power BI, NLTK, NumPy, Open Neural Network Exchange, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, R, scikit-learn, SciPy, Scrapy, SQL, Tableau, TensorFlow, TextBlob, Word2vecWhat's included
| Service Tiers |
Starter
$20
|
Standard
$30
|
Advanced
$50
|
|---|---|---|---|
| Delivery Time | 1 day | 2 days | 3 days |
Number of Revisions | 1 | 2 | 2 |
Number of Model Variations | 1 | 2 | 2 |
Number of Scenarios | 1 | 1 | 1 |
Number of Graphs/Charts | 1 | 2 | 2 |
Model Validation/Testing | |||
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code |
About Jamshaid
Professional Python NLP and ML Services for Your Projects
Hyderabad City, Pakistan - 5:49 pm local time
Machine Learning Expertise:
Naive Bayes
Decision Tree
Logistic Regression
Support Vector Machine
Knearest Neighbor (KNN)
Linear Regression, Ridge, Lasso
Random Forest, Adaboost, Xgboost, Gradient Boost, Bagging
NLP Techniques:
Tokenization
Text Similarity
Text Cleaning
Vectorization
Ngram Analysis
TFIDF
Lemmatization
Stemming
POS Tagging
Information Retrieval
Handling Categorical Data
Feature Engineering
Sentiment Analysis
Preferred Platforms:
Jupyter Notebook
Google Colab
Pycharm
Tools Utilized:
Pandas
Numpy
Regular Expression
NLTK
Spacy
Seaborn, Matplotlib, Plotly
Neattext
Scikitlearn, Keras, TensorFlow
Imblearn, JSON
Flask, Streamlit, Tkinter
Project Specialization:
Python Programming Tasks
Data Visualization
Data Cleaning, Analysis
Statistical Analysis
Natural Language Processing
Sentiment Analysis (Twitter, Reddit)
Deep Learning (ANN, CNN, RNN, LSTM)
Why Choose Us?
Guaranteed Client Satisfaction
Timely Delivery
Unmatched Quality
Steps for completing your project
After purchasing the project, send requirements so Jamshaid can start the project.
Delivery time starts when Jamshaid receives requirements from you.
Jamshaid works on your project following the steps below.
Revisions may occur after the delivery date.
Client purchases the project and sends requirements.
Model name? deadline for a project?