Video wird geladen...

Video konnte nicht geladen werden

Beim Laden dieses Videos ist ein Problem aufgetreten. Dies könnte an einem vorübergehenden Netzwerkproblem liegen oder das Video ist möglicherweise nicht verfügbar.

Oracle offering free certificate training in A.I and Machine learning

𝗘𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 𝗣𝗹𝘂𝗴𝘀🔌🔌

67,303 subscribers

57,585 Aufrufe • vor 1 Jahr •via X (Twitter)

Wissenschaft & Technologie Nachrichten & Politik Bildung

Anya Rossi• Live Now

Private livecam show

9 Kommentare

Profilbild von Baba Voss Tich

Baba Voss Tichvor 1 Jahr

Since nobody wants to Google these days....

Profilbild von 𝗘𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 𝗣𝗹𝘂𝗴𝘀🔌🔌

𝗘𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 𝗣𝗹𝘂𝗴𝘀🔌🔌vor 1 Jahr

🤣🤣🤣

Profilbild von Kamohelo

Kamohelovor 1 Jahr

Where's the link?

Profilbild von Sarcastic_Badass😎

Sarcastic_Badass😎vor 1 Jahr

Yeah it's free but to collect that certificate you will have to pay up

Profilbild von Zozo🇿🇦

Zozo🇿🇦vor 1 Jahr

@TJMUNGONI

Profilbild von Uncle Knights

Uncle Knightsvor 1 Jahr

Thank you for this, im already flying through the course

Profilbild von LambChip

LambChipvor 1 Jahr

We hear you, my sista. Thank you

Profilbild von Zamo Mbuyisa

Zamo Mbuyisavor 1 Jahr

Link please

Profilbild von Sarcastic_Badass😎

Sarcastic_Badass😎vor 1 Jahr

They love plugging people with stuff they haven't tried before showing people

Ähnliche Videos

New Graduate Certificate and Masters Degree in Machine Learning and Artificial Intelligence for Engineering at University of Washington!!! 🧠💪🧠

New Graduate Certificate and Masters Degree in Machine Learning and Artificial Intelligence for Engineering at University of Washington!!! 🧠💪🧠

Steven Brunton

12,846 Aufrufe • vor 1 Jahr

AWS offering 100% free certification vouchers for Foundational and Associate certifications. These vouchers cover the following certifications: Cloud Practitioner, AI Practitioner, Solutions Architect, SysOps Administrator, Developer, Data Engineer, and Machine Learning Engineer.

AWS offering 100% free certification vouchers for Foundational and Associate certifications. These vouchers cover the following certifications: Cloud Practitioner, AI Practitioner, Solutions Architect, SysOps Administrator, Developer, Data Engineer, and Machine Learning Engineer.

Hawa

189,721 Aufrufe • vor 1 Jahr

Lean Applied Machine Learning for FREE by Cornell University - 80 Lectures - Lecture Notes - Self-paced Learning - 100% FREE Course and Notes link 🧵👇

Lean Applied Machine Learning for FREE by Cornell University - 80 Lectures - Lecture Notes - Self-paced Learning - 100% FREE Course and Notes link 🧵👇

Python Space

121,264 Aufrufe • vor 3 Jahren

Free Machine Learning with Python Course from IBM Topic covered: - Supervised Learning - Unsupervised Learning - Dimensionality Reduction & Collaborative Filtering 100% FREE Course link 🧵👇

Free Machine Learning with Python Course from IBM Topic covered: - Supervised Learning - Unsupervised Learning - Dimensionality Reduction & Collaborative Filtering 100% FREE Course link 🧵👇

Afiz ⚡️

59,880 Aufrufe • vor 3 Jahren

Trump: Oracle will be building a $14 billion worth of cloud computing and A.I. infrastructure in the kingdom. Why isn't he doing that here, David?

Trump: Oracle will be building a $14 billion worth of cloud computing and A.I. infrastructure in the kingdom. Why isn't he doing that here, David?

Acyn

21,957 Aufrufe • vor 3 Monaten

Jim Simons explaining Machine Learning in Finance:

Jim Simons explaining Machine Learning in Finance:

ₕₐₘₚₜₒₙ

29,476 Aufrufe • vor 5 Monaten

“Each Factory And Each Machine Is For Multiple Industries” Kevin Czinger Discusses Revolutionary A.I. Development

“Each Factory And Each Machine Is For Multiple Industries” Kevin Czinger Discusses Revolutionary A.I. Development

Bannon’s WarRoom

19,696 Aufrufe • vor 1 Jahr

KL divergence is a fundamental concept used in machine learning, from optimization a neural net to RL training of LLMs. but here is what it actually means:

KL divergence is a fundamental concept used in machine learning, from optimization a neural net to RL training of LLMs. but here is what it actually means:

ℏεsam

20,381 Aufrufe • vor 5 Monaten

2. Sololearn / Sololearn → Sololearn provides AI-powered web design and app development training, as well as free data analysis tools. In addition, you may earn credentials while learning.

2. Sololearn / Sololearn → Sololearn provides AI-powered web design and app development training, as well as free data analysis tools. In addition, you may earn credentials while learning.

Mujeeb Ahmed

27,461 Aufrufe • vor 1 Jahr

As AI advances towards mainstream adoption, security and privacy in machine learning models must be prioritized Our founder Dawn Song shares why security in machine learning systems is crucial as we begin to use AI for everyday purposes

As AI advances towards mainstream adoption, security and privacy in machine learning models must be prioritized Our founder Dawn Song shares why security in machine learning systems is crucial as we begin to use AI for everyday purposes

Oasis Labs

20,270 Aufrufe • vor 3 Jahren

Artificial Intelligence and machine learning, data scientists and analysts top list of future jobs in demand by 2025. Branji #HigherEducationExpoAndCareerFair

Artificial Intelligence and machine learning, data scientists and analysts top list of future jobs in demand by 2025. Branji #HigherEducationExpoAndCareerFair

NTV Kenya

76,906 Aufrufe • vor 2 Jahren

Dave Allen offering advice and training Johnny Fisher earlier today. They fought each other in May 🤝

Dave Allen offering advice and training Johnny Fisher earlier today. They fought each other in May 🤝

Boxing Kingdom

89,907 Aufrufe • vor 1 Jahr

Still after all these years I’m experimenting with pattens. Many of which are the result of my constant training with A.I. to better understand what I am capable of. Machine Inspired phrases # 10023

Still after all these years I’m experimenting with pattens. Many of which are the result of my constant training with A.I. to better understand what I am capable of. Machine Inspired phrases # 10023

Harry Yeff

11,101 Aufrufe • vor 3 Jahren

.const believes Bittensor will outpace centralized machine learning labs, becoming the go-to hub for efficient problem-solving in data collection, benchmarks, and AI training. As competitors emerge, $TAO aims to remain the Schelling point for digital commodity systems.

.const believes Bittensor will outpace centralized machine learning labs, becoming the go-to hub for efficient problem-solving in data collection, benchmarks, and AI training. As competitors emerge, $TAO aims to remain the Schelling point for digital commodity systems.

Grayscale

102,100 Aufrufe • vor 1 Jahr

A unique first of its kind CM Skills Development prog. 4000 students today started training in market demand driven courses like Graphic Design (UI- UX Design),Data Analytics ,Cyber Security,Game Development, AI and Machine Learning & Cloud Computing. #PioneeringITSolutions

A unique first of its kind CM Skills Development prog. 4000 students today started training in market demand driven courses like Graphic Design (UI- UX Design),Data Analytics ,Cyber Security,Game Development, AI and Machine Learning & Cloud Computing. #PioneeringITSolutions

Maryam Nawaz Sharif

85,758 Aufrufe • vor 2 Jahren

Building a machine learning model isn’t just about finding the right algorithm—it’s about the right process. In Machine Learning in Production, Andrew Ng breaks down the iterative loop of model development: training, error analysis, refining hyperparameters, and improving data. Getting to a high test set accuracy is one thing, but aligning your model with real-world business metrics? That’s where the real challenge begins. Learn how to bridge the gap between models and impact:

Building a machine learning model isn’t just about finding the right algorithm—it’s about the right process. In Machine Learning in Production, Andrew Ng breaks down the iterative loop of model development: training, error analysis, refining hyperparameters, and improving data. Getting to a high test set accuracy is one thing, but aligning your model with real-world business metrics? That’s where the real challenge begins. Learn how to bridge the gap between models and impact:

DeepLearning.AI

45,248 Aufrufe • vor 1 Jahr

Meet the AI agents that search, reason, and sift through all your content to get you answers grounded in your team’s shared context. Hear more from Dropbox machine learning engineer Jongmin Baek—along with machine learning engineer Marta Mendez—on Working Smarter.

Meet the AI agents that search, reason, and sift through all your content to get you answers grounded in your team’s shared context. Hear more from Dropbox machine learning engineer Jongmin Baek—along with machine learning engineer Marta Mendez—on Working Smarter.

Dropbox

19,515 Aufrufe • vor 13 Tagen

if you're struggling on where to start learning ML, here’s a playlist of 30 youtube videos to learn machine learning fundamentals from scratch "Machine Learning: Teach by Doing" is a solid choice to learn both theory and code. (1) Introduction to Machine Learning Teach by Doing: (2) What is Machine Learning? History of Machine Learning: (3) Types of ML Models: (4) 6 steps of any ML project: (5) Install Python and VSCode and run your first code: (6) Linear Classifiers Part 1: (7) Linear Classifiers Part 2: (8) Jupyter Notebook, Numpy and Scikit-Learn: (9) Running the Random Linear Classifier Algorithm in Python: (10) The oldest ML model - Perceptron: (11) Coding the Perceptron: (12) Perceptron Convergence Theorem: (13) Magic of features in Machine Learning: (14) One hot encoding: (15) Logistic Regression Part 1: (16) Cross Entropy Loss: (17) How gradient descent works: (18) Logistic Regression from scratch in Python: (19) Introduction to Regularization: (20) Implementing Regularization in Python: (21) Linear Regression Introduction: (22) Ordinary Least Squares step by step implementation: (23) Ridge regression fundamentals and intuition: (24) Regression recap for interviews: (25) Neural network architecture in 30 minutes: (26) Backpropagation intuition: (27) Neural network activation functions: (28) Momentum in gradient descent: (29) Hands on neural network training in Python: (30) Introduction to Convolutional Neural Networks (CNNs):

if you're struggling on where to start learning ML, here’s a playlist of 30 youtube videos to learn machine learning fundamentals from scratch "Machine Learning: Teach by Doing" is a solid choice to learn both theory and code. (1) Introduction to Machine Learning Teach by Doing: (2) What is Machine Learning? History of Machine Learning: (3) Types of ML Models: (4) 6 steps of any ML project: (5) Install Python and VSCode and run your first code: (6) Linear Classifiers Part 1: (7) Linear Classifiers Part 2: (8) Jupyter Notebook, Numpy and Scikit-Learn: (9) Running the Random Linear Classifier Algorithm in Python: (10) The oldest ML model - Perceptron: (11) Coding the Perceptron: (12) Perceptron Convergence Theorem: (13) Magic of features in Machine Learning: (14) One hot encoding: (15) Logistic Regression Part 1: (16) Cross Entropy Loss: (17) How gradient descent works: (18) Logistic Regression from scratch in Python: (19) Introduction to Regularization: (20) Implementing Regularization in Python: (21) Linear Regression Introduction: (22) Ordinary Least Squares step by step implementation: (23) Ridge regression fundamentals and intuition: (24) Regression recap for interviews: (25) Neural network architecture in 30 minutes: (26) Backpropagation intuition: (27) Neural network activation functions: (28) Momentum in gradient descent: (29) Hands on neural network training in Python: (30) Introduction to Convolutional Neural Networks (CNNs):

ℏεsam

108,861 Aufrufe • vor 1 Jahr

a playlist of 30 youtube videos to learn machine learning fundamentals from scratch if you're struggling on where to start learning ML, this list goes this "Machine Learning: Teach by Doing" is a solid choice to learn both theory and code. (1) Introduction to Machine Learning Teach by Doing: (2) What is Machine Learning? History of Machine Learning: (3) Types of ML Models: (4) 6 steps of any ML project: (5) Install Python and VSCode and run your first code: (6) Linear Classifiers Part 1: (7) Linear Classifiers Part 2: (8) Jupyter Notebook, Numpy and Scikit-Learn: (9) Running the Random Linear Classifier Algorithm in Python: (10) The oldest ML model - Perceptron: (11) Coding the Perceptron: (12) Perceptron Convergence Theorem: (13) Magic of features in Machine Learning: (14) One hot encoding: (15) Logistic Regression Part 1: (16) Cross Entropy Loss: (17) How gradient descent works: (18) Logistic Regression from scratch in Python: (19) Introduction to Regularization: (20) Implementing Regularization in Python: (21) Linear Regression Introduction: (22) Ordinary Least Squares step by step implementation: (23) Ridge regression fundamentals and intuition: (24) Regression recap for interviews: (25) Neural network architecture in 30 minutes: (26) Backpropagation intuition: (27) Neural network activation functions: (28) Momentum in gradient descent: (29) Hands on neural network training in Python: (30) Introduction to Convolutional Neural Networks (CNNs):

a playlist of 30 youtube videos to learn machine learning fundamentals from scratch if you're struggling on where to start learning ML, this list goes this "Machine Learning: Teach by Doing" is a solid choice to learn both theory and code. (1) Introduction to Machine Learning Teach by Doing: (2) What is Machine Learning? History of Machine Learning: (3) Types of ML Models: (4) 6 steps of any ML project: (5) Install Python and VSCode and run your first code: (6) Linear Classifiers Part 1: (7) Linear Classifiers Part 2: (8) Jupyter Notebook, Numpy and Scikit-Learn: (9) Running the Random Linear Classifier Algorithm in Python: (10) The oldest ML model - Perceptron: (11) Coding the Perceptron: (12) Perceptron Convergence Theorem: (13) Magic of features in Machine Learning: (14) One hot encoding: (15) Logistic Regression Part 1: (16) Cross Entropy Loss: (17) How gradient descent works: (18) Logistic Regression from scratch in Python: (19) Introduction to Regularization: (20) Implementing Regularization in Python: (21) Linear Regression Introduction: (22) Ordinary Least Squares step by step implementation: (23) Ridge regression fundamentals and intuition: (24) Regression recap for interviews: (25) Neural network architecture in 30 minutes: (26) Backpropagation intuition: (27) Neural network activation functions: (28) Momentum in gradient descent: (29) Hands on neural network training in Python: (30) Introduction to Convolutional Neural Networks (CNNs):

ℏεsam

117,570 Aufrufe • vor 1 Jahr

Neural networks explained from first principles: how simple linear pieces combine into richer models, and why layered representations make machine learning more powerful. MIT OpenCourseWare, 6.036 Introduction to Machine Learning, Fall 2020.

Neural networks explained from first principles: how simple linear pieces combine into richer models, and why layered representations make machine learning more powerful. MIT OpenCourseWare, 6.036 Introduction to Machine Learning, Fall 2020.

tetsuo

10,720 Aufrufe • vor 1 Monat