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  • Mathematical Foundations For Deep Learning

Results for "mathematical+foundations+for+deep+learning"


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    U

    University of Pittsburgh

    Mathematical Foundations for Data Science and Analytics

    Skills you'll gain: Statistical Analysis, NumPy, Probability Distribution, Matplotlib, Plot (Graphics), Statistics, Data Science, Probability & Statistics, Probability, Statistical Modeling, Predictive Modeling, Data Analysis, Linear Algebra, Predictive Analytics, Statistical Methods, Mathematics and Mathematical Modeling, Applied Mathematics, Python Programming, Machine Learning, Logical Reasoning

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    3.8
    Rating, 3.8 out of 5 stars
    ·
    12 reviews

    Beginner · Specialization · 1 - 3 Months

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    D

    DeepLearning.AI

    Mathematics for Machine Learning and Data Science

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Statistical Methods, Probability Distribution, Linear Algebra, Statistical Inference, Model Optimization, Machine Learning Methods, Statistics, Applied Mathematics, Probability, Calculus, Dimensionality Reduction, Applied Machine Learning, Mathematical Software, Data Transformation, Machine Learning

    4.6
    Rating, 4.6 out of 5 stars
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    3.2K reviews

    Intermediate · Specialization · 1 - 3 Months

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    E

    Edureka

    Neural Networks and Computer Vision Foundations

    Skills you'll gain: Computer Vision, Image Analysis, Model Evaluation, Convolutional Neural Networks, Model Optimization, Artificial Neural Networks, Model Training, Machine Learning Methods, PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Transfer Learning, Machine Learning, Recurrent Neural Networks (RNNs), Artificial Intelligence, NumPy, Python Programming, Matplotlib, Data Visualization, Data Science

    Beginner · Course · 1 - 4 Weeks

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    I

    Imperial College London

    Mathematics for Machine Learning

    Skills you'll gain: Dimensionality Reduction, Linear Algebra, Regression Analysis, NumPy, Calculus, Unsupervised Learning, Applied Mathematics, Statistical Methods, Descriptive Statistics, Model Optimization, Mathematical Software, Jupyter, Statistics, Numerical Analysis, Applied Machine Learning, Geometry, Artificial Neural Networks, Data Science, Data Manipulation, Data Transformation

    4.6
    Rating, 4.6 out of 5 stars
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    15K reviews

    Beginner · Specialization · 3 - 6 Months

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    J

    Johns Hopkins University

    Foundations of Neural Networks

    Skills you'll gain: Responsible AI, Autoencoders, Model Training, Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Data Ethics, Model Optimization, Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Generative Adversarial Networks (GANs), Machine Learning Algorithms, Model Deployment, Generative Model Architectures, Debugging, Machine Learning Methods, Artificial Intelligence, Image Analysis, Unsupervised Learning

    4.5
    Rating, 4.5 out of 5 stars
    ·
    24 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
    New
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    D

    Dartmouth College

    Practical Machine Learning: Foundations to Neural Networks

    Skills you'll gain: Supervised Learning, Bayesian Network, Logistic Regression, Artificial Neural Networks, Machine Learning Methods, Statistical Modeling, Predictive Modeling, Model Evaluation, Convolutional Neural Networks, Statistical Machine Learning, Probability & Statistics, Bayesian Statistics, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, Statistical Methods, Artificial Intelligence, Regression Analysis, Statistical Inference

    Build toward a degree

    Intermediate · Specialization · 3 - 6 Months

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    J

    Johns Hopkins University

    Foundational Mathematics for AI

    Skills you'll gain: Descriptive Statistics, Linear Algebra, Exploratory Data Analysis, Data-Driven Decision-Making, Data Analysis, Bayesian Statistics, Artificial Intelligence, Probability, Regression Analysis, Mathematical Software, Calculus, Advanced Mathematics, Applied Mathematics, Probability Distribution, Mathematical Modeling, Model Optimization, Integral Calculus, Algebra, Machine Learning Algorithms, Dimensionality Reduction

    4.9
    Rating, 4.9 out of 5 stars
    ·
    10 reviews

    Beginner · Course · 1 - 3 Months

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    B

    Birla Institute of Technology & Science, Pilani

    Mathematics for Engineering

    Skills you'll gain: Data Analysis, Computational Logic, Integral Calculus, Trigonometry, Linear Algebra, Engineering Analysis, Logical Reasoning, Deductive Reasoning, Probability & Statistics, Statistical Analysis, Calculus, Statistical Methods, Analysis, Advanced Mathematics, Bayesian Statistics, Statistical Inference, Theoretical Computer Science, Mathematics and Mathematical Modeling, Numerical Analysis, Descriptive Analytics

    4.5
    Rating, 4.5 out of 5 stars
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    196 reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: New
    New
    P

    Packt

    Modern Deep Learning Foundations

    Skills you'll gain: Model Deployment, Deep Learning, Model Optimization, Model Training, Convolutional Neural Networks, PyTorch (Machine Learning Library), Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Computer Vision, Recurrent Neural Networks (RNNs), Model Evaluation, Artificial Neural Networks, Natural Language Processing

    Intermediate · Course · 1 - 3 Months

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    C

    Coursera

    Foundations of Machine Learning

    Skills you'll gain: Model Evaluation, Supervised Learning, Unsupervised Learning, Data Preprocessing, Time Series Analysis and Forecasting, Applied Machine Learning, Model Training, Machine Learning Methods, Machine Learning Algorithms, Statistical Machine Learning, Feature Engineering, Machine Learning Software, Dimensionality Reduction, Machine Learning, Predictive Modeling, Data Wrangling, Predictive Analytics, Scikit Learn (Machine Learning Library), Classification Algorithms, Forecasting

    4.5
    Rating, 4.5 out of 5 stars
    ·
    15 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    Introduction to Deep Learning & Neural Networks with Keras

    Skills you'll gain: Keras (Neural Network Library), Deep Learning, Transfer Learning, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Model Optimization, Machine Learning Methods, Image Analysis, Applied Machine Learning, Autoencoders, Model Training, Regression Analysis, Network Architecture, Natural Language Processing, Machine Learning

    4.7
    Rating, 4.7 out of 5 stars
    ·
    2.1K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    P

    Packt

    Foundations of Deep Reinforcement Learning with PyTorch

    Skills you'll gain: PyTorch (Machine Learning Library), Reinforcement Learning, Deep Learning, Machine Learning Methods, Artificial Neural Networks, Model Training, Machine Learning, Machine Learning Algorithms, Model Optimization, Python Programming, Algorithms, Model Evaluation

    Intermediate · Course · 1 - 3 Months

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In summary, here are 10 of our most popular mathematical+foundations+for+deep+learning courses

  • Mathematical Foundations for Data Science and Analytics: University of Pittsburgh
  • Mathematics for Machine Learning and Data Science: DeepLearning.AI
  • Neural Networks and Computer Vision Foundations: Edureka
  • Mathematics for Machine Learning: Imperial College London
  • Foundations of Neural Networks: Johns Hopkins University
  • Practical Machine Learning: Foundations to Neural Networks: Dartmouth College
  • Foundational Mathematics for AI: Johns Hopkins University
  • Mathematics for Engineering: Birla Institute of Technology & Science, Pilani
  • Modern Deep Learning Foundations: Packt
  • Foundations of Machine Learning: Coursera

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