#mathsforml search results
Day 9 of #365DaysofML - Countable Sets - Uncountable Sets - Random Variable #Probability #MathsForML #Day9 #MLFoundations
Machine Learning is cool, but can you handle the math behind it? 📊🤖 #AI #MachineLearning #MathsForML
Solved some linear algebra quizzes today using python and Numpy library. #mathsforML #machinelearning #AI
Post angle: Math powers every ML algorithm. Without it, ML is just a black box. #MathsForML #100DaysOfML #DeepLearning #MachineLearning #AI
Day 10 of #365DaysofML - Probability - Practiced questions based on Random variables involving Sigma Field. - Cumulative Distribution Function - Linear Algebra - Types of Matrices - Practice Questions #MathsforML #Day10
Day 13 of #365DaysOfML - Probability & Statistics - Marginal PMF of Discrete Random Variables - Conditional Distribution of one random variable given another - Linear Algebra - System of Linear Equations Basics - Some Determinant Basics #MathsforML #Probability
Day 5 of #365DaysofML: - Explored Conditional Probability. - Studied Independence of Events. - Understood Pairwise Independence. - Learned about Mutual Independence. Continuing to strengthen my understanding of probability for better ML models. #ProbabilityDeepDive #MathsforML
Just a reminder for #MathsForML Upcoming class tomorrow (16/12/19) at 1900 JST/1530 IST/1000 GMT from @__MLT__
Day 3 of #100DaysOfMLToday I revised vectors 🔹 Scalar = “how much” (5 km) 🔹 Vector = “how much + which way” (5 km north) 🔹 Invariant across coordinate systems 🔹 Basis gives meaning (like language to letters) Vectors = how ML represents data. #MachineLearning #MathsForML
Building a robust mathematical foundation for ML. #LinearAlgebraBasics #MLBasics #MathsforML
Day 15 of #365DaysofML Solved some problems on the concepts of Joint PMF, Marginal PMF and Conditional PMF. #MathsforML #Day15 #Probability #Statistics #MachineLearning
Day 8 of #365DaysOfML - Repeated independent trial - Bernoulli Distribution - Binomial Distribution - Geometric Distribution #Probability #MathsForML #MLBasics #Day8
You can build ML models with libraries. But if you don’t understand the math behind them, you’re just stacking blocks blindfolded. Libraries are tools. Math is vision. #mathsforml #machinelearning #maths
Day 8/60 - Linear Algebra Basics Vectors, matrices, and how they shape ML. Just the start, but feels powerful! #AI #ML #MathsForML 📐🧠💻
Day 12 of #365DaysofML - Learnt about the concept of Multiple Random Variables. - Studied Joint PMF - Solved some examples on joint PMF. #MathsforML #Day12 #Probability #MachineLearning
Day 11 of #365DaysofML Probability - Distribution Function - Learnt how is distribution function related to cdf. Linear Algebra - Solved Questions based on Matrices. #MathsforML #Day11 #Probability
Day 8 of 60 days of Data Scienec and ML Series where we covered Maths for ML : Linear Algrebra, Calculus, Matrix and Vectors, Bayes Theorem and Cheatsheets medium.datadriveninvestor.com/day-8-60-days-… #mathsforml
Post angle: Math powers every ML algorithm. Without it, ML is just a black box. #MathsForML #100DaysOfML #DeepLearning #MachineLearning #AI
Day 3 of #100DaysOfMLToday I revised vectors 🔹 Scalar = “how much” (5 km) 🔹 Vector = “how much + which way” (5 km north) 🔹 Invariant across coordinate systems 🔹 Basis gives meaning (like language to letters) Vectors = how ML represents data. #MachineLearning #MathsForML
You can build ML models with libraries. But if you don’t understand the math behind them, you’re just stacking blocks blindfolded. Libraries are tools. Math is vision. #mathsforml #machinelearning #maths
Solved some linear algebra quizzes today using python and Numpy library. #mathsforML #machinelearning #AI
Day 8/60 - Linear Algebra Basics Vectors, matrices, and how they shape ML. Just the start, but feels powerful! #AI #ML #MathsForML 📐🧠💻
Machine Learning is cool, but can you handle the math behind it? 📊🤖 #AI #MachineLearning #MathsForML
Day 15 of #365DaysofML Solved some problems on the concepts of Joint PMF, Marginal PMF and Conditional PMF. #MathsforML #Day15 #Probability #Statistics #MachineLearning
Day 13 of #365DaysOfML - Probability & Statistics - Marginal PMF of Discrete Random Variables - Conditional Distribution of one random variable given another - Linear Algebra - System of Linear Equations Basics - Some Determinant Basics #MathsforML #Probability
Day 12 of #365DaysofML - Learnt about the concept of Multiple Random Variables. - Studied Joint PMF - Solved some examples on joint PMF. #MathsforML #Day12 #Probability #MachineLearning
Day 11 of #365DaysofML Probability - Distribution Function - Learnt how is distribution function related to cdf. Linear Algebra - Solved Questions based on Matrices. #MathsforML #Day11 #Probability
Day 10 of #365DaysofML - Probability - Practiced questions based on Random variables involving Sigma Field. - Cumulative Distribution Function - Linear Algebra - Types of Matrices - Practice Questions #MathsforML #Day10
Day 9 of #365DaysofML - Countable Sets - Uncountable Sets - Random Variable #Probability #MathsForML #Day9 #MLFoundations
Day 8 of #365DaysOfML - Repeated independent trial - Bernoulli Distribution - Binomial Distribution - Geometric Distribution #Probability #MathsForML #MLBasics #Day8
Day 5 of #365DaysofML: - Explored Conditional Probability. - Studied Independence of Events. - Understood Pairwise Independence. - Learned about Mutual Independence. Continuing to strengthen my understanding of probability for better ML models. #ProbabilityDeepDive #MathsforML
Building a robust mathematical foundation for ML. #LinearAlgebraBasics #MLBasics #MathsforML
Day 9 of #365DaysofML - Countable Sets - Uncountable Sets - Random Variable #Probability #MathsForML #Day9 #MLFoundations
Machine Learning is cool, but can you handle the math behind it? 📊🤖 #AI #MachineLearning #MathsForML
Solved some linear algebra quizzes today using python and Numpy library. #mathsforML #machinelearning #AI
Day 10 of #365DaysofML - Probability - Practiced questions based on Random variables involving Sigma Field. - Cumulative Distribution Function - Linear Algebra - Types of Matrices - Practice Questions #MathsforML #Day10
Day 13 of #365DaysOfML - Probability & Statistics - Marginal PMF of Discrete Random Variables - Conditional Distribution of one random variable given another - Linear Algebra - System of Linear Equations Basics - Some Determinant Basics #MathsforML #Probability
Day 5 of #365DaysofML: - Explored Conditional Probability. - Studied Independence of Events. - Understood Pairwise Independence. - Learned about Mutual Independence. Continuing to strengthen my understanding of probability for better ML models. #ProbabilityDeepDive #MathsforML
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