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In this Applied Machine Learning & Data Science Recipe (Jupyter Notebook), the reader will find the practical use of applied machine learning and data science in R programming:

ML Classification in Python | Data Science Tutorials | Tensorflow | Keras | IRIS | Deep Learning.

### What should I learn from this Applied Machine Learning & Data Science tutorials?

You will learn:

- ML Classification in Python | Data Science Tutorials | Tensorflow | Keras | IRIS | Deep Learning.
- Practical Data Science tutorials with R for Beginners and Citizen Data Scientists.
- Practical Machine Learning tutorials with R for Beginners and Machine Learning Developers.

**For Citizen Data Scientists and Machine Learning Developers**: **Download 1000+ End-to-End Applied Machine Learning & Data Science Notebooks in Python and R for Beginners to Professionals**.

Latest end-to-end Learn by Coding Recipes in Project-Based Learning:

**All Notebooks in One Bundle: Data Science Recipes and Examples in Python & R****. **

**End-to-End Python Machine Learning Recipes & Examples.**

**End-to-End R Machine Learning Recipes & Examples.**

**Applied Statistics with R for Beginners and Business Professionals**

**Data Science and Machine Learning Projects in Python: Tabular Data Analytics**

**Data Science and Machine Learning Projects in R: Tabular Data Analytics**

**Python Machine Learning & Data Science Recipes: Learn by Coding**

**R Machine Learning & Data Science Recipes: Learn by Coding**

**Comparing Different Machine Learning Algorithms in Python for Classification (FREE)**

ML Classification in Python | Data Science Tutorials | Tensorflow | Keras | IRIS | Deep Learning:

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**Call for Jupyter Notebook Challenge**: Business Data Science & Machine Learning (Classification, Regression and Forecasting) @ **https://wacamlds.podia.com**

We are very pleased to let you know that WACAMLDS (**https://wacamlds.podia.com**) is hosting Jupyter Notebook Challenges for Business Data Science & Machine Learning. The author(s) of the best notebook will receive a prize valued $150 USD.

For details criteria and eligibility, please see below:

**Theme**: Jupyter Notebook Challenge for Business Data Science & Machine Learning (Classification, Regression and Forecasting). You can choose any dataset to present your notebook.

**Eligibility**: Only WACAMLDS members can participate (either FREE member or Gold member).

**Submission Format**:

- a) Your notebook must be submitted as .html file as export from Jupyter notebook or Jupyter lab. Choose any language – Python or R or Julia (with or without SQL).
- b) No need to submit any dataset(s) along with the submission file (.html).
- c) First cell of the notebook must have a title, author(s) name, affiliation and email address of corresponding author.
- d) Second cell of the notebook must have a very brief description of the dataset used.
- e) Remaining cells (input and output) should have your end-to-end analysis, model development, results etc.

**How to submit**: visit **WACAMLDS** website for details.

**Prize & Benefit**:

- a) $150 USD
- b) Certificate of Achievement
- c) Share the winner details and the best notebook to the data scientist professional groups.
- d) Top ranked notebooks will be available through WACAMLDS.

Download End-to-End Notebooks in Python and R for Citizen Data Scientists and Machine Learning Developers from **https://wacamlds.podia.com/end-to-end-notebooks-for-citizen-data-scientists?coupon=WACAMLDS80**

**Introduction to Applied Machine Learning & Data Science for Beginners, Business Analysts, Students, Researchers and Freelancers with Python & R Codes @ Western Australian Center for Applied Machine Learning & Data Science (WACAMLDS) !!!**