Data Scientist

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Service Description

Unlock the power of data with comprehensive data science and machine learning solutions! As a skilled practitioner in Python, I specialize in a wide range of cutting-edge techniques, including NLP, computer vision, classification, regression, clustering, market basket analysis, and reinforcement learning.
With a deep understanding of statistical analysis, data preprocessing, and feature engineering, I have the expertise to tackle complex data challenges head-on. I employ Python's robust libraries and frameworks to extract meaningful insights and develop predictive models that drive data-driven decision-making.
In the realm of Natural Language Processing (NLP), I harness the capabilities of Python to analyze and interpret textual data. From sentiment analysis to text classification and entity recognition, I create powerful NLP models that unveil valuable information from unstructured text.
In the realm of computer vision, I leverage Python's image processing libraries to build state-of-the-art models for image classification,face recognition, and image segmentation. These models enable accurate image recognition and understanding, opening up a world of possibilities for automated visual analysis.
Whether your needs revolve around supervised learning or unsupervised learning, I have you covered. I employ a variety of machine learning algorithms, including decision trees, support vector machines, random forests, and deep learning models, to deliver accurate predictions and uncover patterns hidden within your data.
But it doesn't end there. I am well-versed in advanced techniques such as reinforcement learning, where I train intelligent agents to make optimal decisions in dynamic environments. By leveraging reinforcement learning libraries, I empower your business to optimize processes and maximize efficiency.
Throughout the project lifecycle, I prioritize clear communication and collaboration. I work closely with you to understand your specific goals and tailor solutions to your unique requirements. I provide regular updates, insightful visualizations, and detailed reports to ensure transparency and demonstrate the progress made.
By harnessing the power of Python, I transform raw data into actionable insights, enabling you to make informed decisions and drive business growth. Ready to embark on a data-driven journey? Let's connect and unlock the full potential of your data with cutting-edge data science and machine learning solutions. Contact me today to get started!

Services:
✅ Classification
✅ Regression
✅ Clustering
✅ Market Basket Analysis or Association Rule Mining
✅ Named Entity Recognition or NER
✅ Text Classification
✅ Language Translation
✅ Masked Language Modelling or MLM
✅ Text Summarization
✅ Next Word Prediction or Language Modelling
✅ Question Answering
✅ Image Classification
✅ Exploratory Data Analysis
✅ Data Analytics

Some libraries & ML models I use:
✅ Transformers
✅ Chatgpt
✅ Open AI
✅ Decision Tree Regression
✅ Random Forest Regression
✅ Artificial Neural Network

Why me?
✅ Fast Delivery
✅ Fast Response

Technology Used

Transformers
Openai
ChatGPT
Keras
Scikit Learn
TensorFlow

Frequently Asked Questions

Q1. Do you provide data analytics and data visualization services?

A. Yes I provide data analytics and data visualization services to turn data into actionable insights for forecasting and other purposes.

Q2. Which natural language processing techniques and models do you normally use?

A. I use stemming tokenization | lemmatization | word2vec | ngrams and word embedding among other techniques. Some models I use are recurrent neural networks | LSTM
| bidirectional LSTM RNN among other pretrained models | transfer learning techniques and libraries.

Q3. Can you do a sentiment analysis task?
A. Yes I can.

Q4. Do you use Jupyter Notebook or Google Colab Notebook for your projects?

A. Depending on the type of project, I normally switch between both of the above. Google colab is specifically helpful in deep learning tasks.

Q5. Which libraries do you normally use?
A. I normally use numpy | pandas | tensorflow | keras | matplotlib | seaborn | sklearn & pytorch among other libraries.

Q6. Which algorithms do you normally use?
A. The choice of algorithm depends upon the type of task at hand. I normally use use support vector machines | convolutional neural networks | k means clustering | k nearest neighbor | decision tree classifier | random forest classifier | support vector regression | lasso regression | support vector classifier | DBSCAN clustering | Naïve Bayes | CNN | linear regression & logistic regression among others.

Q7. Which computer vision tasks can you do?
A. I can do image classification | image segmentation | face recognition & image processing .

Q8. Which data preprocessing techniques do you use?
A. Some of the data preprocessing techniques I normally use are standardization | scaling | normalization | handling missing values | removing duplicates | identifying outliers | feature engineering | feature extraction | feature selection | dimensionality reduction | visualization graphs, | density Plots | wisker plots | correlation matrix | histograms and box Plots .

Irtaza Ahmed
Lahore, PK.
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Tags

data science machine learning nlp natural language processing ml computer vision

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