Machine Learning For Dummies

Index

• Machine Learning For Dummies

- Index - Episode 1: A Pythonic Hope - E1: Information - E1: Contents - Episode 2: Python Strikes Back - E2: Information - E2: Contents - Episode 3: Return of the Tensor - E3: Information - E3: Contents - Dates :calendar: - Show Some :heart:

Episode 1: A Pythonic Hope

E1: Information

• Type: Talk
• Level: Beginner
• Duration: 2-3 Hours with a Break
• Prerequisites: Little bits of programming knowledge may help you understand some of the horrible jokes I make
• Technical Requirements: None
• Materials:

- Jupyter Notebook - PDF - [COMING SOON]

E1: Contents

• Machine What?

- Don't believe the hype - GG EZ - The Data Jedi Path

• Python: Learning to love Snakes

- General overwiew of the language - Pythonic Syntax and Style - Pythonic Objects - Strings' Theory - Python as a calculator - Logical Python - Lists - Tuples - Dictionaries - The Code Must Flow - Functions - Import Antigravity - Python Mind Tricks

• Use Python Luke!

- Royal Rumble - The Python Data/Scientific Ecosystem - Kong Fu Pandas [COMING SOON] - Data Plumbing - Data Porn - WE ARE LEGION - From Dask till dawn [COMING SOON] - Twinke twinkle little Spark [COMING SOON] - 010010 TOTALLY NOT A CHAPTER ON ROBOTS - END OF TRANSMISSION [COMING SOON] - De Naturalis Lingua [COMING SOON]

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Episode 2: Python Strikes Back

E2: Information

• Type: Workshop
• Level: Beginner - Intermediate
• Duration: 2-3 Hours with a Break
• Prerequisites: Basic Python Notions (see Episode 1: A Pythonic Hope)
• Technical Requirements:

- Docker - Custom Docker Image (COMING SOON) - GitHub Account - Join the machine-learning-for-dummies Gitter Room for all communications and technical discussion regarding the Machine Learning for Dummies series! - Watch (and if you like it :star:) the Machine Learning For Dummies Repo

• Materials:

- Docker Lightning talk pdf - Custom Docker Image - [COMING SOON] - Jupyter Notebook - [COMING SOON]

E2: Contents

• Why we like whales: Introduction to docker by @federicoB
• Enter the Mad Scientist lab: IPython + Jupyter (lab)
• Numpy and the Masters of the vector-verse: From lists to vector
• Of Snakes and Pandas: Pandas Dataframe 101
• Nom Nom Nom: Ingesting Data
• Pandarellas - Becoming Cinderellas with Pandas 1: Cleaning
• Pandarellas - Becoming Cinderellas with Pandas 2: Transformation
• Bow Chicka Wow Wow: Introduction to Data Porn (also known as Data Visualization)

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Episode 3: Return of the Tensor

E3: Information

• Type: Talk
• Level: Intermediate
• Duration: 2-3 Hours with a Break
• Prerequisites: Numpy and Pandas basics
• Materials:

- Introduction to Machine Learning - Deep Learning introduction with Tensorflow

E3: Contents

• Introduction to Machine Learning

0. What is Machine Learning? 1. Why Use Machine Learning? 2. Types of Machine Learning 3. Supervised Learning 4. Unsupervised Learning 5. Semi-Supervised Learning 6. Reinforcement Learning 7. Machine Learning Challenges

• Glimpsing at: scikit-learn [COMING SOON]

- An exceptional API [COMING SOON] - Machine Learning true Workhorse [COMING SOON] - Showcase: Diabetes [COMING SOON]

• Deep Learning introduction with Tensorflow by @galeone

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Dates :calendar:

• [x] 25/11/2017 - Episode 1: A Pythonic Hope - @ImpactHub, Reggio Emilia, Italy
• [x] 30/11/2017 - Episode 1: A Pythonic Hope - @LuogoComune, Bologna, Italy
• [x] 30/01/2018 - Episode 2: Python Strikes Back - @LuogoComune, Bologna, Italy
• [x] 20/02/2018 - Episode 2: Python Strikes Back Remastered [Replica] - @LuogoComune, Bologna, Italy
• [x] 22/06/2018 - Episode 3: Return of the Tensor - @LuogoComune, Bologna, Italy

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