How you SHOULD code Machine Learning

CodeEmporium · Beginner ·📐 ML Fundamentals ·5y ago
Skills: ML Pipelines90%

Key Takeaways

End-to-End Machine Learning Pipeline using scikit-learn and Kite AI-powered coding assistant

Original Description

End-to-End Machine Learning Pipeline with scikit learn. Pipelines are sick! SPONSOR Kite is a free AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I've been using Kite. Love it! Learn more here: https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=codeemporium&utm_content=description-only CODE: https://github.com/ajhalthor/scikit-learn-pipeline
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1 Linear Regression and Multiple Regression
Linear Regression and Multiple Regression
CodeEmporium
2 Logistic Regression - THE MATH YOU SHOULD KNOW!
Logistic Regression - THE MATH YOU SHOULD KNOW!
CodeEmporium
3 Generative Adversarial Networks - FUTURISTIC & FUN AI !
Generative Adversarial Networks - FUTURISTIC & FUN AI !
CodeEmporium
4 Deep Learning on the Cloud - GPU TO LEARN FASTER
Deep Learning on the Cloud - GPU TO LEARN FASTER
CodeEmporium
5 Deep Mind's AlphaGo Zero - EXPLAINED
Deep Mind's AlphaGo Zero - EXPLAINED
CodeEmporium
6 Mask Region based Convolution Neural Networks - EXPLAINED!
Mask Region based Convolution Neural Networks - EXPLAINED!
CodeEmporium
7 Attention in Neural Networks
Attention in Neural Networks
CodeEmporium
8 Depthwise Separable Convolution - A FASTER CONVOLUTION!
Depthwise Separable Convolution - A FASTER CONVOLUTION!
CodeEmporium
9 One Neural network learns EVERYTHING ?!
One Neural network learns EVERYTHING ?!
CodeEmporium
10 Neural Voice Cloning
Neural Voice Cloning
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11 AI creates Image Classifiers…by DRAWING?
AI creates Image Classifiers…by DRAWING?
CodeEmporium
12 Unpaired Image-Image Translation using CycleGANs
Unpaired Image-Image Translation using CycleGANs
CodeEmporium
13 K-Means Clustering - EXPLAINED!
K-Means Clustering - EXPLAINED!
CodeEmporium
14 Random Forest Classification
Random Forest Classification
CodeEmporium
15 Data Science in Finance
Data Science in Finance
CodeEmporium
16 Hypothesis testing with Applications in Data Science
Hypothesis testing with Applications in Data Science
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17 A/B Testing - Simply Explained
A/B Testing - Simply Explained
CodeEmporium
18 The Kernel Trick - THE MATH YOU SHOULD KNOW!
The Kernel Trick - THE MATH YOU SHOULD KNOW!
CodeEmporium
19 Support Vector Machines - THE MATH YOU  SHOULD KNOW
Support Vector Machines - THE MATH YOU SHOULD KNOW
CodeEmporium
20 Principal Component Analysis (PCA) - THE MATH YOU SHOULD KNOW!
Principal Component Analysis (PCA) - THE MATH YOU SHOULD KNOW!
CodeEmporium
21 History of Calculus - Animated
History of Calculus - Animated
CodeEmporium
22 Curiosity in AI
Curiosity in AI
CodeEmporium
23 DropBlock - A BETTER DROPOUT for Neural Networks
DropBlock - A BETTER DROPOUT for Neural Networks
CodeEmporium
24 Autoencoders - EXPLAINED
Autoencoders - EXPLAINED
CodeEmporium
25 Recurrent Neural Networks - EXPLAINED!
Recurrent Neural Networks - EXPLAINED!
CodeEmporium
26 LSTM Networks - EXPLAINED!
LSTM Networks - EXPLAINED!
CodeEmporium
27 Building an Image Captioner with Neural Networks
Building an Image Captioner with Neural Networks
CodeEmporium
28 10 Machine Learning Questions - ANSWERED!
10 Machine Learning Questions - ANSWERED!
CodeEmporium
29 How do neural networks work?
How do neural networks work?
CodeEmporium
30 Evolution of Face Generation |  Evolution of GANs
Evolution of Face Generation | Evolution of GANs
CodeEmporium
31 How does Google Translate's AI work?
How does Google Translate's AI work?
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32 How to keep up with AI research?
How to keep up with AI research?
CodeEmporium
33 How does YouTube recommend videos? - AI EXPLAINED!
How does YouTube recommend videos? - AI EXPLAINED!
CodeEmporium
34 Variational Autoencoders - EXPLAINED!
Variational Autoencoders - EXPLAINED!
CodeEmporium
35 Logistic Regression - VISUALIZED!
Logistic Regression - VISUALIZED!
CodeEmporium
36 Gradient Descent - THE MATH YOU SHOULD KNOW
Gradient Descent - THE MATH YOU SHOULD KNOW
CodeEmporium
37 Boosting - EXPLAINED!
Boosting - EXPLAINED!
CodeEmporium
38 Transformer Neural Networks - EXPLAINED! (Attention is all you need)
Transformer Neural Networks - EXPLAINED! (Attention is all you need)
CodeEmporium
39 Loss Functions - EXPLAINED!
Loss Functions - EXPLAINED!
CodeEmporium
40 Optimizers - EXPLAINED!
Optimizers - EXPLAINED!
CodeEmporium
41 NLP with Neural Networks & Transformers
NLP with Neural Networks & Transformers
CodeEmporium
42 Batch Normalization - EXPLAINED!
Batch Normalization - EXPLAINED!
CodeEmporium
43 Activation Functions - EXPLAINED!
Activation Functions - EXPLAINED!
CodeEmporium
44 Data Scientist Answers Interview Questions
Data Scientist Answers Interview Questions
CodeEmporium
45 Why use GPU with Neural Networks?
Why use GPU with Neural Networks?
CodeEmporium
46 How do GPUs speed up Neural Network training?
How do GPUs speed up Neural Network training?
CodeEmporium
47 BERT Neural Network - EXPLAINED!
BERT Neural Network - EXPLAINED!
CodeEmporium
48 ConvNets Scaled Efficiently
ConvNets Scaled Efficiently
CodeEmporium
49 Transformer Neural Net makes music! (JukeboxAI)
Transformer Neural Net makes music! (JukeboxAI)
CodeEmporium
50 What do filters of Convolution Neural Network learn?
What do filters of Convolution Neural Network learn?
CodeEmporium
51 We're hosting a Machine Learning Conference!
We're hosting a Machine Learning Conference!
CodeEmporium
52 MLconfEU 2020: Machine Learning Conference for Software Engineers
MLconfEU 2020: Machine Learning Conference for Software Engineers
CodeEmporium
53 Are Neural Networks Intelligent?
Are Neural Networks Intelligent?
CodeEmporium
54 Time Series Forecasting with Machine Learning
Time Series Forecasting with Machine Learning
CodeEmporium
55 Few Shot Learning - EXPLAINED!
Few Shot Learning - EXPLAINED!
CodeEmporium
56 How does a Data Scientist Fight FRAUD?
How does a Data Scientist Fight FRAUD?
CodeEmporium
57 How would a Data Scientist analyze Customer Churn?
How would a Data Scientist analyze Customer Churn?
CodeEmporium
58 Expectations with Machine Learning
Expectations with Machine Learning
CodeEmporium
59 Why Logistic Regression DOESN'T return probabilities?!
Why Logistic Regression DOESN'T return probabilities?!
CodeEmporium
How you SHOULD code Machine Learning
How you SHOULD code Machine Learning
CodeEmporium

This video teaches how to code Machine Learning using scikit-learn and showcases the benefits of using pipelines. It also introduces Kite AI, a free AI-powered coding assistant that helps with smart completions and documentation.

Key Takeaways
  1. Install scikit-learn
  2. Import necessary libraries
  3. Build a pipeline
  4. Train a model
  5. Evaluate the model
  6. Use Kite AI for coding assistance
💡 Using pipelines in Machine Learning can simplify the workflow and improve efficiency, and tools like Kite AI can enhance the coding experience.

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