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  • Using The Protodash Algorithm


Results for "using the protodash algorithm"


  • Status: Free
    Free
    T

    The Chinese University of Hong Kong

    离散优化算法篇 Solving Algorithms for Discrete Optimization

    Skills you'll gain: Operations Research, Applied Mathematics, Algorithms, Mathematical Modeling, Combinatorics, Computational Logic, Advanced Mathematics, Performance Tuning, Theoretical Computer Science, Simulations, Linear Algebra

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    M

    Microsoft

    AI and Machine Learning Algorithms and Techniques

    Skills you'll gain: Unsupervised Learning, Generative AI, Large Language Modeling, Supervised Learning, Deep Learning, LLM Application, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Reinforcement Learning, Predictive Modeling, Machine Learning Algorithms, Artificial Neural Networks, Feature Engineering, Model Evaluation, Convolutional Neural Networks, Data Preprocessing, Dimensionality Reduction

    4.7
    Rating, 4.7 out of 5 stars
    ·
    60 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Algorithms for DNA Sequencing

    Skills you'll gain: Bioinformatics, Molecular Biology, Computational Thinking, Data Structures, Python Programming, Data Analysis, Algorithms, Life Sciences

    4.7
    Rating, 4.7 out of 5 stars
    ·
    932 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Minnesota

    Optimization for Decision Making

    Skills you'll gain: Operations Research, Mathematical Modeling, Business Modeling, Business Analytics, Analytics, Data Modeling, Business Mathematics, Process Optimization, Data-Driven Decision-Making, Microsoft Excel, Decision Making, Linear Algebra, Spreadsheet Software, Graphing

    4.7
    Rating, 4.7 out of 5 stars
    ·
    90 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    S

    Stanford University

    Divide and Conquer, Sorting and Searching, and Randomized Algorithms

    Skills you'll gain: Algorithms, Graph Theory, Data Structures, Theoretical Computer Science, Computational Thinking, Analysis, Computer Science, Probability

    4.8
    Rating, 4.8 out of 5 stars
    ·
    5.3K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Dynamic Programming, Greedy Algorithms

    Skills you'll gain: Theoretical Computer Science, Algorithms, Computational Thinking, Pseudocode, Data Structures, Design Strategies, Programming Principles, Computer Science, Advanced Mathematics, Python Programming, Analysis

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    245 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    S

    Simplilearn

    Introduction Course to Autoencoders, VAEs, and GANs

    Skills you'll gain: Generative Adversarial Networks (GANs), Generative AI, Autoencoders, Deep Learning, Convolutional Neural Networks, Tensorflow, Unsupervised Learning, Dimensionality Reduction, Model Evaluation

    Beginner · Course · 1 - 4 Weeks

  • C

    Coursera

    Deep Learning with PyTorch : Generative Adversarial Network

    Skills you'll gain: Generative Adversarial Networks (GANs), PyTorch (Machine Learning Library), Deep Learning, Convolutional Neural Networks, Image Analysis, Python Programming

    4.5
    Rating, 4.5 out of 5 stars
    ·
    99 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Preview
    Preview
    L

    Ludwig-Maximilians-Universität München (LMU)

    Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python

    Skills you'll gain: Finite Element Methods, Numerical Analysis, Engineering Analysis, Jupyter, Engineering Calculations, Differential Equations, Applied Mathematics, Mathematical Modeling, Distributed Computing, Python Programming, Mechanics, Vibrations, Simulations

    4.8
    Rating, 4.8 out of 5 stars
    ·
    391 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    D

    DeepLearning.AI

    Повышение эффективности глубоких нейросетей

    Skills you'll gain: Tensorflow, Deep Learning, Data Compilation, Data Preprocessing, Artificial Neural Networks, Model Evaluation, Performance Tuning, Machine Learning Algorithms, Machine Learning

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Colorado System

    Abstraction, Problem Decomposition, and Functions

    Skills you'll gain: Computational Thinking, C (Programming Language), Data Structures, Programming Principles, Computer Programming, Program Development, Data Storage, Debugging

    4.6
    Rating, 4.6 out of 5 stars
    ·
    37 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    P

    Pearson

    Programming Generative AI: Unit 1

    Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Generative Model Architectures, Multimodal Prompts, Artificial Neural Networks, Deep Learning, Large Language Modeling, Tensorflow, Convolutional Neural Networks

    Intermediate · Course · 1 - 4 Weeks

1…456…834

In summary, here are 10 of our most popular using the protodash algorithm courses

  • 离散优化算法篇 Solving Algorithms for Discrete Optimization: The Chinese University of Hong Kong
  • AI and Machine Learning Algorithms and Techniques: Microsoft
  • Algorithms for DNA Sequencing: Johns Hopkins University
  • Optimization for Decision Making: University of Minnesota
  • Divide and Conquer, Sorting and Searching, and Randomized Algorithms: Stanford University
  • Dynamic Programming, Greedy Algorithms: University of Colorado Boulder
  • Introduction Course to Autoencoders, VAEs, and GANs: Simplilearn
  • Deep Learning with PyTorch : Generative Adversarial Network: Coursera
  • Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python: Ludwig-Maximilians-Universität München (LMU)
  • Повышение эффективности глубоких нейросетей: DeepLearning.AI

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