- A computer/phone
- An internet connection
- Very basic Python knowledge
- Willingness to learn
What you do not need:
- Complex math
- An expensive computer
- A PhD
Math will come later on in your machine learning journey :)
(2 / 15)
A simple guide on how to train your first neural network in under 10 minutes to kick-start your machine learning journey.
(+ no setup required and free extra resources)
๐งต๐
- A computer/phone
- An internet connection
- Very basic Python knowledge
- Willingness to learn
What you do not need:
- Complex math
- An expensive computer
- A PhD
Math will come later on in your machine learning journey :)
(2 / 15)
(3 / 15)
(4 / 15)
๐//colab.research.google.com/drive/1FxSrY6hwdgszzNydyobTLsMyO0bfpiPs?usp=sharing
(6 / 15)
1. We import TensorFlow and Keras which are frameworks for making neural nets
2. Our Neural Net: This is where all the magic happens, for this exercise we need only one neuron.
Wait! What is a neural net?๐
(7 / 15)
In these neural networks, data flows through them and each neuron (the circle) has a numerical value which will change.
(8 / 15)
Think of the neurons as dials on a lock, you have to tune every dial to open the lock.
(9 / 15)
Once the dials are well tuned, you have a well trained neural network!
...
(10 / 15)
3. Now we pass the data (flats and prices) through our neural network 500 times. (these loops are called epochs)
(11 / 15)
And that's it! It was that easy.
In case you want to improve your python and machine learning skills after this exercise, these are great frfee courses to take ๐
(12 / 15)
More from Pratham Prasoon
This is a step-by-step guide on getting started with Python as a total beginner.
(includes free resources and everything else you need to get started)
๐งต๐
Before we begin, I want to congratulate you on your decision to learn how to code using Python.
I still remember how I wrote my first piece of code 6 years and all the amazing and cool things I've been able to do with it ever since.
(2 / 24)
Make sure to keep in mind that it is probably best for you to keep your expectations in check.
Don't expect to make AAA games or state of the art machine learning models in a week.
(3 / 24)
Programming is not something that you can learn in a single week, it takes consistent effort and dedication over time to get good at it.
With all that being said, let's dive straight in.
(4 / 24)
In order to write Python code, you'll need to install Python on your system.
Linux and macOS users can skip this step because they come pre-installed with Python.
Download link: https://t.co/KSZ4Qd6CNk
(5 / 24)
(includes free resources and everything else you need to get started)
๐งต๐
Before we begin, I want to congratulate you on your decision to learn how to code using Python.
I still remember how I wrote my first piece of code 6 years and all the amazing and cool things I've been able to do with it ever since.
(2 / 24)
Make sure to keep in mind that it is probably best for you to keep your expectations in check.
Don't expect to make AAA games or state of the art machine learning models in a week.
(3 / 24)
Programming is not something that you can learn in a single week, it takes consistent effort and dedication over time to get good at it.
With all that being said, let's dive straight in.
(4 / 24)
In order to write Python code, you'll need to install Python on your system.
Linux and macOS users can skip this step because they come pre-installed with Python.
Download link: https://t.co/KSZ4Qd6CNk
(5 / 24)
More from Machine learning
This is a Twitter series on #FoundationsOfML.
โ Today, I want to start discussing the different types of Machine Learning flavors we can find.
This is a very high-level overview. In later threads, we'll dive deeper into each paradigm... ๐๐งต
Last time we talked about how Machine Learning works.
Basically, it's about having some source of experience E for solving a given task T, that allows us to find a program P which is (hopefully) optimal w.r.t. some metric
According to the nature of that experience, we can define different formulations, or flavors, of the learning process.
A useful distinction is whether we have an explicit goal or desired output, which gives rise to the definitions of 1๏ธโฃ Supervised and 2๏ธโฃ Unsupervised Learning ๐
1๏ธโฃ Supervised Learning
In this formulation, the experience E is a collection of input/output pairs, and the task T is defined as a function that produces the right output for any given input.
๐ The underlying assumption is that there is some correlation (or, in general, a computable relation) between the structure of an input and its corresponding output and that it is possible to infer that function or mapping from a sufficiently large number of examples.
โ Today, I want to start discussing the different types of Machine Learning flavors we can find.
This is a very high-level overview. In later threads, we'll dive deeper into each paradigm... ๐๐งต
Last time we talked about how Machine Learning works.
Basically, it's about having some source of experience E for solving a given task T, that allows us to find a program P which is (hopefully) optimal w.r.t. some metric
I'm starting a Twitter series on #FoundationsOfML. Today, I want to answer this simple question.
— Alejandro Piad Morffis (@AlejandroPiad) January 12, 2021
\u2753 What is Machine Learning?
This is my preferred way of explaining it... \U0001f447\U0001f9f5
According to the nature of that experience, we can define different formulations, or flavors, of the learning process.
A useful distinction is whether we have an explicit goal or desired output, which gives rise to the definitions of 1๏ธโฃ Supervised and 2๏ธโฃ Unsupervised Learning ๐
1๏ธโฃ Supervised Learning
In this formulation, the experience E is a collection of input/output pairs, and the task T is defined as a function that produces the right output for any given input.
๐ The underlying assumption is that there is some correlation (or, in general, a computable relation) between the structure of an input and its corresponding output and that it is possible to infer that function or mapping from a sufficiently large number of examples.
10 PYTHON ๐ libraries for machine learning.
Retweets are appreciated.
[ Thread ]
1. NumPy (Numerical Python)
- The most powerful feature of NumPy is the n-dimensional array.
- It contains basic linear algebra functions, Fourier transforms, and tools for integration with other low-level languages.
Ref: https://t.co/XY13ILXwSN
2. SciPy (Scientific Python)
- SciPy is built on NumPy.
- It is one of the most useful libraries for a variety of high-level science and engineering modules like discrete Fourier transform, Linear Algebra, Optimization, and Sparse matrices.
Ref: https://t.co/ALTFqM2VUo
3. Matplotlib
- Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
- You can also use Latex commands to add math to your plot.
- Matplotlib makes hard things possible.
Ref: https://t.co/zodOo2WzGx
4. Pandas
- Pandas is for structured data operations and manipulations.
- It is extensively used for data munging and preparation.
- Pandas were added relatively recently to Python and have been instrumental in boosting Pythonโs usage.
Ref: https://t.co/IFzikVHht4
Retweets are appreciated.
[ Thread ]
1. NumPy (Numerical Python)
- The most powerful feature of NumPy is the n-dimensional array.
- It contains basic linear algebra functions, Fourier transforms, and tools for integration with other low-level languages.
Ref: https://t.co/XY13ILXwSN
2. SciPy (Scientific Python)
- SciPy is built on NumPy.
- It is one of the most useful libraries for a variety of high-level science and engineering modules like discrete Fourier transform, Linear Algebra, Optimization, and Sparse matrices.
Ref: https://t.co/ALTFqM2VUo
3. Matplotlib
- Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
- You can also use Latex commands to add math to your plot.
- Matplotlib makes hard things possible.
Ref: https://t.co/zodOo2WzGx
4. Pandas
- Pandas is for structured data operations and manipulations.
- It is extensively used for data munging and preparation.
- Pandas were added relatively recently to Python and have been instrumental in boosting Pythonโs usage.
Ref: https://t.co/IFzikVHht4
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๐ฟ๐ป๐๐ ๐๐๐๐๐ ๐๐ ๐ ๐บ๐๐๐ : ๐ซ๐๐๐๐๐ & ๐ฝ๐๐๐๐๐
Once upon a time there was a Raja named Uttฤnapฤda born of Svayambhuva Manu,1st man on earth.He had 2 beautiful wives - Suniti & Suruchi & two sons were born of them Dhruva & Uttama respectively.
#talesofkrishna https://t.co/E85MTPkF9W
Now Suniti was the daughter of a tribal chief while Suruchi was the daughter of a rich king. Hence Suruchi was always favored the most by Raja while Suniti was ignored. But while Suniti was gentle & kind hearted by nature Suruchi was venomous inside.
#KrishnaLeela
The story is of a time when ideally the eldest son of the king becomes the heir to the throne. Hence the sinhasan of the Raja belonged to Dhruva.This is why Suruchi who was the 2nd wife nourished poison in her heart for Dhruva as she knew her son will never get the throne.
One day when Dhruva was just 5 years old he went on to sit on his father's lap. Suruchi, the jealous queen, got enraged and shoved him away from Raja as she never wanted Raja to shower Dhruva with his fatherly affection.
Dhruva protested questioning his step mother "why can't i sit on my own father's lap?" A furious Suruchi berated him saying "only God can allow him that privilege. Go ask him"
Once upon a time there was a Raja named Uttฤnapฤda born of Svayambhuva Manu,1st man on earth.He had 2 beautiful wives - Suniti & Suruchi & two sons were born of them Dhruva & Uttama respectively.
#talesofkrishna https://t.co/E85MTPkF9W
Prabhu says i reside in the heart of my bhakt.
— Right Singh (@rightwingchora) December 21, 2020
Guess the event. pic.twitter.com/yFUmbfe5KL
Now Suniti was the daughter of a tribal chief while Suruchi was the daughter of a rich king. Hence Suruchi was always favored the most by Raja while Suniti was ignored. But while Suniti was gentle & kind hearted by nature Suruchi was venomous inside.
#KrishnaLeela
The story is of a time when ideally the eldest son of the king becomes the heir to the throne. Hence the sinhasan of the Raja belonged to Dhruva.This is why Suruchi who was the 2nd wife nourished poison in her heart for Dhruva as she knew her son will never get the throne.
One day when Dhruva was just 5 years old he went on to sit on his father's lap. Suruchi, the jealous queen, got enraged and shoved him away from Raja as she never wanted Raja to shower Dhruva with his fatherly affection.
Dhruva protested questioning his step mother "why can't i sit on my own father's lap?" A furious Suruchi berated him saying "only God can allow him that privilege. Go ask him"
