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Harshad Patil's Projects

10-steps-to-become-a-data-scientist icon 10-steps-to-become-a-data-scientist

📢 Ready to learn or review your knowledge! You will learn 10 skills as data scientist: 📚 Python, Machine Learning, Deep Learning, Data Cleaning, EDA, python packages such as Numpy, Pandas, Seaborn, Matplotlib, Plotly, Tensorfolw, Theano...., Linear Algebra, Big Data, Analysis Tools and solve some real problems such as predict house prices.

applied-ml icon applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

data-science icon data-science

:bar_chart: Path to a free self-taught education in Data Science!

data-science-1 icon data-science-1

An open source Data Science repository to learn and apply towards solving real world problems.

data-science-ipython-notebooks icon data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

homemade-machine-learning icon homemade-machine-learning

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

learning-resources icon learning-resources

A collection of pdfs and ebooks about Operating Systems, Machine Learning, Cloud System Adminstration etc.

machine-learning-practice icon machine-learning-practice

This repository would contain working machine learning programs developed in Python. I will make use of various open source datasets available over the internet.

machine-learning-workflow-with-python icon machine-learning-workflow-with-python

This is a comprehensive ML techniques with python: Define the Problem- Specify Inputs & Outputs- Data Collection- Exploratory data analysis -Data Preprocessing- Model Design- Training- Evaluation

ml-from-scratch icon ml-from-scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

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