📐 ML Fundamentals

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

ML Fundamentals

Create Basic Conversational AI Chatbot using RASA NLU

Krish Naik Intermediate 6y ago

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How To Learn Maths For Data Science By Self Study And For Free

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Codebasics Live Q & A - Feb 19, 2020

codebasics Beginner 6y ago

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Feistel Cipher - Computerphile

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This Neural Network Turns Videos Into 60 FPS!

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Why Are Time Series Special? : Time Series Talk

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Codility CyclicRotation Python

Aladdin Persson Beginner 6y ago

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Codility BinaryGap Python

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Scott Aaronson: Quantum Computing | Lex Fridman Podcast #72

Lex Fridman Beginner 6y ago

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3 Proven Data Science Projects for Beginners (Kaggle)

Ken Jee Beginner 6y ago

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Ben Eater Intermediate 6y ago

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Complete Statistical Theory of Learning (Vladimir Vapnik) | MIT Deep Learning Series

Lex Fridman Beginner 6y ago

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Computerphile Intermediate 6y ago

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DEMO - Get Started with Machine Learning at the Edge

The New Stack Beginner 6y ago

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Adversarial Explanations

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What is Classification | Introduction to Machine Learning for beginners | The Most Used Terms 8

What's AI by Louis-François Bouchard Beginner 6y ago

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Python Machine Learning Tutorial #8 - Handwritten Digit Recognition with Tensorflow

NeuralNine Beginner 6y ago

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PyTorch Tutorial 15 - Transfer Learning

Patrick Loeber Beginner 6y ago

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CUDA Neural Networks

Siraj Raval Beginner 6y ago

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Impact Measurement - Innovations and Tensions

Saïd Business School, University of Oxford Intermediate 6y ago

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AI for Agriculture and Global Food Security with Nemo Semret - #347

The TWIML AI Podcast with Sam Charrington Beginner 6y ago

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Python Machine Learning Tutorial #7 - Neural Networks

NeuralNine Beginner 6y ago

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What is Reinforcement Learning | Machine Learning basics explained for beginners 7

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PyTorch Tutorial 14 - Convolutional Neural Network (CNN)

Patrick Loeber Beginner 6y ago

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The Oxford Bank Governance Programme at Saïd Business School

Saïd Business School, University of Oxford Intermediate 6y ago

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University of Illinois Master of Computer Science & MCS in Data Science Admissions Webinar

Coursera Beginner 6y ago

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How Convolutions Work (TensorFlow in Practice)

DeepLearningAI Beginner 6y ago

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Special Announcement: Approaching (almost) any machine learning problem

Abhishek Thakur Beginner 6y ago

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Neural Structured Learning - Part 3: Training with synthesized graphs

TensorFlow Beginner 6y ago

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How To Learn Statistics By Self Study And For Free

Krish Naik Beginner 6y ago

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Skillset Of Data Scientist In 2020 (Do not Miss this Video)

Krish Naik Intermediate 6y ago

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Weighted Interval Scheduling Python Code

Aladdin Persson Intermediate 6y ago

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Interval Scheduling Greedy Algorithm: Python

Aladdin Persson Intermediate 6y ago

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How To Translate Business Ideas Into Data Science Solutions

Krish Naik Intermediate 6y ago

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Advance House Price Prediction-Feature Selection

Krish Naik Advanced 6y ago

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Vladimir Vapnik: Predicates, Invariants, and the Essence of Intelligence | Lex Fridman Podcast #71

Lex Fridman Beginner 6y ago

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Skillset Of Data Analyst in 2020

Krish Naik Intermediate 6y ago

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Python Sudoku Solver - Computerphile

Computerphile Intermediate 6y ago

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Live Q&A Join Our Affordable AI Course

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Practical Differential Privacy at LinkedIn with Ryan Rogers - #346

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Networking Optimizations for Multi-Node Deep Learning on Kubernetes with Erez Cohen - #345

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Data Science & Machine Learning Fundamentals

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Deep Learning and Advanced Techniques

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Foundations of Statistical Learning & Algorithms

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AI Applications in People Management

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Image Captioning with TensorFlow & Streamlit

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Numerical Methods for Engineers

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Demand Forecasting Using Time Series

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KI für alle

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Introduction to Linear Algebra

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Calculus for Machine Learning and Data Science

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Prepare for DP-100: Data Science on Microsoft Azure Exam

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Essential Causal Inference Techniques for Data Science

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Process Mining: Data science in Action

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Amazon Kinesis Video Streams - Getting Started

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Fake News Detection with Machine Learning

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K-Means Clustering 101: World Happiness Report

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Machine Learning for Engineers: Algorithms and Applications

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Automate ML Pipelines for Peak Performance

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