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-# MEDIUM_NoteBook
-Repository containing notebooks of my posts on [MEDIUM](https://medium.com/@cerlymarco).
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+Author: Marco Cerliani
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-To be notified every time a new post is published, **SUBSCRIBE [HERE](https://medium.com/subscribe/@cerlymarco)**.
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-[](https://www.buymeacoffee.com/cerlymarco)
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+Objective
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+Arrange my 
posts and accompanying code in a clear and concise manner, enabling easy access for readers who may wish to reuse the code.
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+About Me
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+I am a statistician with a deep understanding of artificial intelligence and machine learning. I have devoted my career to the exploration and advancement of these fields, and my passion for statistical modeling and data analysis has driven me to pursue a role as a data scientist. In addition to my professional work, I also actively engage in writing and sharing my insights on Medium.com. My articles, which focus on a variety of topics related to artificial intelligence and machine learning, are available for view on my Github profile. These pieces are organized and ordered by their most recent publication date with Jupyter Notebook code attached, providing a clear and accessible resource for readers.
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## Posts ordered by most recently publishing date
- PCA for Multivariate Time Series: Forecasting Dynamic High-Dimensional Data [[post](https://medium.com/towards-data-science/pca-for-multivariate-time-series-forecasting-dynamic-high-dimensional-data-ab050a19e8db)]|[[code](https://github.com/cerlymarco/MEDIUM_NoteBook/tree/master/PCA_MultivariateForecasting)]
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- Remaining Life Estimation with Keras [[post](https://towardsdatascience.com/remaining-life-estimation-with-keras-2334514f9c61)]|[[code](https://github.com/cerlymarco/MEDIUM_NoteBook/tree/master/Remaining_Life_Estimation)]
- Quality Control with Machine Learning [[post](https://towardsdatascience.com/quality-control-with-machine-learning-d7aab7382c1e)]|[[code](https://github.com/cerlymarco/MEDIUM_NoteBook/tree/master/Quality_Control)]
- Predictive Maintenance: detect Faults from Sensors with CNN [[post](https://towardsdatascience.com/predictive-maintenance-detect-faults-from-sensors-with-cnn-6c6172613371)]|[[code](https://github.com/cerlymarco/MEDIUM_NoteBook/tree/master/Predictive_Maintenance)]
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+ Installation
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+Setup and install Anaconda and Jupyter Notebook ~ alternatively Google Colab
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+Download Anaconda from https://www.anaconda.com/products/distribution#Downloads selecting defaults
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In Terminal
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+Install Jupyter Notebook
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+Install pip package manager
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+Create environment
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+Ex. env named tf-1.15, installing TensorFlow package version 1.15 in the ipykernel
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+Type
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+to begin!
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+Tip
+To install additional packages
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+conda activate [current env]
+conda install [package]
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