📐 ML Fundamentals

Neural networks, backpropagation, gradient descent — the maths behind AI

ML Fundamentals

How do random forests work?

Abhishek Thakur Beginner 4y ago

ML Fundamentals

Kaggle's 30 Days Of ML (Day-9): First Machine Learning Model and Validation

Abhishek Thakur Beginner 4y ago

ML Fundamentals

Two ways to impute missing values for a categorical feature

Data School Beginner 4y ago

ML Fundamentals

Aggressively Helpful Platform Teams // Stefan Krawczyk // MLOps Coffee Sessions #49

MLOps.community Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

Podcast with Minhaaj Rehman on Data Science and Psychology

Data Professor Beginner 4y ago

ML Fundamentals

My Salary As A Data Scientist From Starting Of My Career

Krish Naik Beginner 4y ago

ML Fundamentals

Building an ML Platform from Scratch: Live Coding Session - Part 2 //Alon Gubkin // MLOps Meetup #74

MLOps.community Beginner 4y ago

ML Fundamentals

Kaggle 30 Days of ML - Day 7 - Python Libraries & Operator Overloading - Learn Python ML in 30 Days

1littlecoder Beginner 4y ago

ML Fundamentals

Kaggle 30 Days of ML - Day 6 - Python String, Dictionary - Learn Python ML in 30 Days

1littlecoder Beginner 4y ago

ML Fundamentals

7 Days Plan To Learn Statistics For Data Analyst And Data Scientist

Krish Naik Beginner 4y ago

ML Fundamentals

W&B Fastbook Reading Group — 9. Training SOTA on ImageNet

Weights & Biases Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

What is the model identifiability problem? | Explained in 60 seconds! | ❓ #AICoffeeBreakQuiz #Shorts

AI Coffee Break with Letitia Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

Best practices for ML product decisions (ML Tech Talks)

TensorFlow Beginner 4y ago

ML Fundamentals

tf serving tutorial | tensorflow serving tutorial | Deep Learning Tutorial 48 (Tensorflow, Python)

codebasics Beginner 4y ago

ML Fundamentals

Use stratified sampling with train_test_split

Data School Beginner 4y ago

ML Fundamentals

Demo your ML models + learn NLP from the best (Hugging Face 🤗) | Machine Learning Monthly July 2021

Daniel Bourke Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

What is Self Supervised Learning?

codebasics Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

Saddle points vs. local minima in high dimensional spaces | ❓ #AICoffeeBreakQuiz #Shorts

AI Coffee Break with Letitia Beginner 4y ago

ML Fundamentals

Neural Networks from Scratch - P.9 Introducing Optimization and derivatives

sentdex Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

Shapley Values : Data Science Concepts

ritvikmath Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

Predicting Urban Land Use

Data Skeptic Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

Colorize Black & White Images in Python

NeuralNine Beginner 4y ago

ML Fundamentals

W&B Study Group: fastai w/ Hugging Face 4/4

Weights & Biases Beginner 4y ago

ML Fundamentals

Ishan Misra: Self-Supervised Deep Learning in Computer Vision | Lex Fridman Podcast #206

Lex Fridman Beginner 4y ago

ML Fundamentals

20. Asynchronous Distributed Algorithms: Shortest-Paths Spanning Trees

MIT OpenCourseWare Beginner 4y ago

ML Fundamentals

What if Data Science was a Building Block? (Dolphyn)

Data Professor Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

What Are Decision Trees And How Do They Work? (From Scratch)

Abhishek Thakur Beginner 4y ago

ML Fundamentals

Kaggle's 30 Days Of ML (Day-8): What is a machine learning model and what is pandas all about?

Abhishek Thakur Beginner 4y ago

ML Fundamentals

Kaggle's 30 Days Of ML (Day-7): Working with external libraries in Python (final python day)

Abhishek Thakur Beginner 4y ago

ML Fundamentals

Kaggle 30 Days of ML - Day 5 - Python Loops, List Comprehension - Learn Python ML in 30 Days

1littlecoder Beginner 4y ago

ML Fundamentals

Kaggle 30 Days of ML - Day 5 - Python List, Tuples - Learn Python ML in 30 Days

1littlecoder Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

Kaggle's 30 Days Of ML (Day-6): Python Strings and Dictionaries

Abhishek Thakur Beginner 4y ago

ML Fundamentals

Kaggle's 30 Days Of ML (Day-5, Part-2): Python Loops and List Comprehension

Abhishek Thakur Beginner 4y ago

ML Fundamentals

Kaggle's 30 Days Of ML (Day-5, Part-1): Python Lists and Tuples

Abhishek Thakur Beginner 4y ago

ML Fundamentals

Kaggle 30 Days of ML - Day 4 - Python Boolean, Conditionals, IF-ELSE - Learn Python ML in 30 Days

1littlecoder Beginner 4y ago

ML Fundamentals

Kaggle's 30 Days Of ML (Day-4): Python Booleans and Conditionals

Abhishek Thakur Beginner 4y ago

ML Fundamentals

Kaggle's 30 Days Of ML (Day-3): Python Functions

Abhishek Thakur Beginner 4y ago

ML Fundamentals

Kaggle 30 Days of ML - Day 3 - Python Functions & Help - Learn Python ML in 30 Days

1littlecoder Beginner 4y ago

ML Fundamentals

Kaggle's 30 Days Of ML (Day-2): Say Hello to Python: variables, types and arithmetic operations

Abhishek Thakur Beginner 4y ago

ML Fundamentals

Kaggle 30 Days of ML - Day 2 - Python Basics - Learn Python ML in 30 Days

1littlecoder Beginner 4y ago

ML Fundamentals

Kaggle 30 Days of ML - Day 1 - Becoming Kaggle Contributor - Learn Python ML in 30 Days

1littlecoder Beginner 4y ago

ML Fundamentals

Kaggle's 30 Days Of ML (Day-1): Getting Started With Kaggle

Abhishek Thakur Beginner 4y ago

ML Fundamentals ⚡ AI Lesson

Prune a decision tree to avoid overfitting

Data School Beginner 4y ago

ML Fundamentals

Analyzing Python Data Quickly with Mito

Krish Naik Beginner 4y ago

ML Fundamentals

30+ Python Practice Problem Set For Data analyst And Data Scientist- Part 1

Krish Naik Beginner 4y ago

ML Fundamentals

Acer Predator Helios 300 With Nvidia RTX 3060 Deep learning Benchmarking, Get The Speed You Want😎🎉😎

Krish Naik Beginner 4y ago

ML Fundamentals

12 days Plan To Learn Python For Data Analyst And Data Science

Krish Naik Beginner 4y ago

ML Fundamentals

How Kaggle Helped Him Become ML Engineer With Mechanical Engineer Degree

codebasics Beginner 4y ago

📚 Coursera Courses Opens on Coursera · Free to audit

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From Zero to Hero - Digital Product Development From Scratch

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Çok değişkenli Fonksiyon II: Uygulamalar / Multivariable Calculus II: Applications

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NumPy, Matplotlib & Pandas – Data Science Prerequisites

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Introduction to AI and Machine Learning on GC - Italiano

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Machine Learning: Clustering & Retrieval

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Data Science in Stratified Healthcare and Precision Medicine

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Master CNNs with Python: Build, Train & Evaluate Models

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Analyze and Build Deep Learning Models with TensorFlow

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Practical Machine Learning on H2O

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Image Classification with Keras: Build & Optimize

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Master Decision Trees in R: Build, Predict & Evaluate

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Optimize and Benchmark AI Algorithms for Speed

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GenAI for Risk Managers: Advanced Risk Analysis Techniques

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Production-Ready Multimodal ML Engineering

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Graphs and Networks

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Introduction to Image Generation - Deutsch

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Power Conversion for Electronic Devices

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No-Code Machine Learning Using Amazon AWS SageMaker Canvas

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