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The Complete Machine Learning Course: From Zero to Expert!

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Lucas Bazilio

14:51:43

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  • 1 - Google Colab for Programming in Python.mp4
    02:52
  • 1 - Google-Colab-for-Programming-in-Python.pdf
  • 2 - Introduction to PCA.mp4
    04:44
  • 2 - Introduction-to-PCA.pdf
  • 3 - Introduction to the Dataset.mp4
    23:05
  • 3 - Introduction-to-the-Dataset.pdf
  • 3 - crabs.csv
  • 3 - introduction-to-the-dataset.zip
  • 4 - Initial Visualization.mp4
    30:16
  • 4 - Initial-Visualization.pdf
  • 4 - crabs.csv
  • 4 - initial-visualization.zip
  • 5 - Using PCA.mp4
    01:05:12
  • 5 - Using-PCA.pdf
  • 5 - pca-in-crabs-dataset.zip
  • 6 - Introduction to LLE.mp4
    02:59
  • 6 - Introduction-to-LLE.pdf
  • 7 - Locally Linear Embedding Algorithm.mp4
    03:39
  • 7 - Locally-Linear-Embedding-Algorithm.pdf
  • 8 - Introduction to the Dataset.mp4
    14:38
  • 8 - Introduction-to-the-Dataset.pdf
  • 8 - crabs.csv
  • 8 - introduction-to-the-dataset.zip
  • 9 - Using LLE.mp4
    27:39
  • 9 - Using-LLE.pdf
  • 9 - crabs.csv
  • 9 - using-locally-linear-embedding.zip
  • 10 - LLE with 3 Dimensions.mp4
    23:38
  • 10 - LLE-with-3-Dimensions.pdf
  • 10 - crabs.csv
  • 10 - lle-with-3-dimensions.zip
  • 11 - Introduction to tSNE.mp4
    05:04
  • 11 - Introduction-to-t-SNE.pdf
  • 12 - Dataset.mp4
    00:47
  • 13 - Introduction to the Dataset.mp4
    14:38
  • 13 - Introduction-to-the-Dataset.pdf
  • 13 - crabs.csv
  • 13 - introduction-to-the-dataset.zip
  • 14 - Using-t-SNE-on-Raw-Data.pdf
  • 14 - tSNE on Raw Data.mp4
    35:09
  • 14 - using-t-sne-with-raw-data.zip
  • 15 - Using-t-SNE-on-Scaled-Data.pdf
  • 15 - tSNE on Scaled Data.mp4
    16:28
  • 15 - using-t-sne-with-scaled-data.zip
  • 16 - Using-t-SNE-on-Standardized-Data.pdf
  • 16 - tSNE on Standardized Data.mp4
    16:56
  • 16 - using-t-sne-with-standardized-data.zip
  • 17 - Introduction to MDS.mp4
    03:18
  • 18 - Multidimensional-Scaling-with-2-Dimensions.pdf
  • 18 - Using MDS with 2 Dimensions.mp4
    20:40
  • 18 - mds-with-2-dimensions.zip
  • 19 - Multidimensional-Scaling-with-3-Dimensions.pdf
  • 19 - Using MDS with 3 Dimensions.mp4
    19:08
  • 19 - mds-with-3-dimensions.zip
  • 20 - Introduccion to ISOMAP.mp4
    02:55
  • 20 - Introduction-to-ISOMAP.pdf
  • 21 - ISOMAP with 2 Dimensions.mp4
    28:59
  • 21 - ISOMAP-with-2-Dimensions.pdf
  • 21 - isomap-with-2-dimensions.zip
  • 22 - ISOMAP with 3 Dimensions.mp4
    27:45
  • 22 - ISOMAP-with-3-Dimensions.pdf
  • 22 - isomap-with-3-dimensions.zip
  • 23 - Introduction to Fisher Discriminant Analysis.mp4
    02:43
  • 24 - Dataset Information.mp4
    00:47
  • 25 - Introduction to the Dataset.mp4
    14:38
  • 25 - Introduction-to-the-Dataset.pdf
  • 25 - crabs.csv
  • 25 - introduction-to-the-dataset.zip
  • 26 - Fisher Discriminant Analysis with 2 Dimensions.mp4
    27:08
  • 26 - Fisher-Discriminant-Analysis-with-2-Dimensions.pdf
  • 26 - fisher-discriminant-analysis-with-2-dimensions.zip
  • 27 - Fisher Discriminant Analysis with 3 Dimensions.mp4
    23:25
  • 27 - Fisher-Discriminant-Analysis-with-3-Dimensions.pdf
  • 27 - fisher-discriminant-analysis-with-3-dimensions.zip
  • 28 - Images.mp4
    00:31
  • 29 - Introduction to Image Dataset.mp4
    17:28
  • 29 - Introduction-to-Image-Dataset.pdf
  • 29 - introduction-to-image-dataset.zip
  • 30 - Fisher Discriminant Analysis.mp4
    25:24
  • 30 - Fisher-Discriminant-Analysis.pdf
  • 30 - fisher-discriminant-analysis.zip
  • 31 - Introduction to the Dataset.mp4
    15:53
  • 31 - Introduction-to-the-Dataset.pdf
  • 31 - LifeExpectancy.csv
  • 31 - introduction-to-the-dataset.zip
  • 32 - Preprocessing.mp4
    28:12
  • 32 - Preprocessing.pdf
  • 32 - preprocessing.zip
  • 33 - Linear Regression.mp4
    32:51
  • 33 - Linear-Regression.pdf
  • 33 - linear-regression.zip
  • 34 - Metrics.mp4
    14:06
  • 34 - Metrics.pdf
  • 34 - metrics.zip
  • 35 - Cross Validation.mp4
    21:55
  • 35 - Cross-Validation.pdf
  • 35 - cross-validation.zip
  • 36 - Ridge Regression and Cross Validation.mp4
    39:22
  • 36 - Ridge-Regression.pdf
  • 37 - Lasso Regression and Cross Validation.mp4
    15:02
  • 37 - Lasso-Regression.pdf
  • 37 - lasso-regression.zip
  • 38 - Analysis.mp4
    17:15
  • 38 - Initial-Analysis.pdf
  • 39 - Data Scaling.mp4
    31:57
  • 39 - Data-Scaling.pdf
  • 39 - scaling-data.zip
  • 40 - OneHot Encoding.mp4
    23:15
  • 40 - One-Hot-Encoding.pdf
  • 40 - one-hot-encoding.zip
  • 41 - Regularization.mp4
    21:19
  • 42 - Final Results.mp4
    13:05
  • 42 - Final-Results.pdf
  • 42 - LifeExpectancy.csv
  • 42 - final-results.zip
  • 43 - Introduction to the Dataset.mp4
    15:09
  • 44 - Partition of the Dataset Train and Test.mp4
    10:17
  • 44 - Partition-of-the-Dataset.pdf
  • 44 - partition-of-dataset.zip
  • 45 - Preprocessing.mp4
    17:17
  • 45 - Preprocessing.pdf
  • 45 - preprocessing.zip
  • 46 - Principal Component Analysis.mp4
    10:41
  • 47 - Linear Discriminant Analysis.mp4
    31:39
  • 47 - Linear-Discriminant-Analysis.pdf
  • 47 - linear-discriminant-analysis.zip
  • 48 - Naive Bayes Classifier.mp4
    17:59
  • 48 - Naive-Bayes-Classifier.pdf
  • 48 - naives-bayes.zip
  • 49 - Quadratic Classifier.mp4
    11:56
  • 49 - Quadratic-Classifier.pdf
  • 49 - quadratic-classifer.zip
  • Description


    Learn Machine Learning in Python from scratch. Everything you need to get the job you want! Code templates included.

    What You'll Learn?


    • Master Machine Learning in Python
    • Become an advanced, confident, and modern Machine Learning developer from scratch
    • Become job-ready by understanding how Machine Learning really works behind the scenes
    • Apply robust Data Science techniques for Machine Learning
    • How to think and work like a data scientist: problem-solving, researching, workflows
    • Get fast and friendly support in the Q&A area
    • Machine Learning fundamentals: Supervised, Unsupervised and Reinforcement Learning
    • Master all Machine Learning python libraries: numpy, scipy, pandas, scikit-learn, matplotlib, seaborn, imblearn, notebook...
    • Handle specific topics like Multilayer Perceptron/Neural Networks, Deep Learning and Clustering
    • Be an expert in Support Vector Machines and Kernels
    • Master Decision Trees/Regression and Combination of Classifiers
    • Practice your skills with 50+ challenges and assignments (solutions included)

    Who is this for?


  • Anyone interested in Machine Learning
  • Any people who have been trying to learn Machine Learning but: 1) still don't really understand it, or 2) still don't feel confident to take a job interview
  • Any students in college who want to start a career in Data Science
  • Anyone interested in working as a Data Scientist
  • Any data analysts who want to level up in Machine Learning
  • Any people who want to create added value to their business by using powerful Machine Learning tools.
  • Anyone who wants to work as a Data Analyst in research, economics, finance, marketing, engineering or medical sectors
  • More details


    Description

    You’ve just stumbled upon the most complete, in-depth Machine Learning course online.

    Whether you want to:

    - build the skills you need to get your first data science job

    - move to a more senior software developer position

    - become a computer scientist mastering in data science

    - or just learn Machine Learning to be able to create your own projects quickly.

    ...this complete Machine Learning Masterclass is the course you need to do all of this, and more.


    This course is designed to give you the machine learning skills you need to become a data science expert. By the end of the course, you will understand the machine learning method extremely well and be able to apply it in your own data science projects and be productive as a computer scientist and developer.


    What makes this course a bestseller?

    Like you, thousands of others were frustrated and fed up with fragmented Youtube tutorials or incomplete or outdated courses which assume you already know a bunch of stuff, as well as thick, college-like textbooks able to send even the most caffeine-fuelled coder to sleep.

    Like you, they were tired of low-quality lessons, poorly explained topics, and confusing info presented in the wrong way. That’s why so many find success in this complete Machine Learning course. It’s designed with simplicity and seamless progression in mind through its content.

    This course assumes no previous data science experience and takes you from absolute beginner core concepts. You will learn the core machine learning skills and master data science. It's a one-stop shop to learn machine learning. If you want to go beyond the core content you can do so at any time.


    What if I have questions?

    As if this course wasn’t complete enough, I offer full support, answering any questions you have.

    This means you’ll never find yourself stuck on one lesson for days on end. With my hand-holding guidance, you’ll progress smoothly through this course without any major roadblocks.


    There’s no risk either!

    This course comes with a guarantee. Meaning if you are not completely satisfied with the course or your progress, simply let me know and I’ll refund you 100%, every last penny no questions asked.

    You either end up with machine learning skills, go on to develop great programs and potentially make an awesome career for yourself, or you try the course and simply get all your money back if you don’t like it…

    You literally can’t lose.


    Moreover, the course is packed with practical exercises that are based on real-life case studies. So not only will you learn the theory, but you will also get lots of hands-on practice building your own models.

    And as a bonus, this course includes Python code templates which you can download and use on your own projects.


    Ready to get started, developer?

    Enroll now using the “Add to Cart” button on the right, and get started on your way to creative, advanced machine learning brilliance. Or, take this course for a free spin using the preview feature, so you know you’re 100% certain this course is for you.

    See you on the inside (hurry, Machine Learning is waiting!)

    Who this course is for:

    • Anyone interested in Machine Learning
    • Any people who have been trying to learn Machine Learning but: 1) still don't really understand it, or 2) still don't feel confident to take a job interview
    • Any students in college who want to start a career in Data Science
    • Anyone interested in working as a Data Scientist
    • Any data analysts who want to level up in Machine Learning
    • Any people who want to create added value to their business by using powerful Machine Learning tools.
    • Anyone who wants to work as a Data Analyst in research, economics, finance, marketing, engineering or medical sectors

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    Lucas Bazilio
    Lucas Bazilio
    Instructor's Courses
    [ENGLISH]Lucas is an expert in mathematics and computer science who from a very young age showed a great passion for teaching.He currently has more than 10 years of experience as a science and technology instructor. He is a specialist in Algorithms, Discrete Mathematics, Artificial Intelligence, Machine Language, among other topics.Lucas is doing research at the prestigious Polytechnic University of Catalonia UPC in Barcelona.Throughout his life, he has given multiple lectures at universities and organizations on the teaching of mathematics.[SPANISH]Lucas es un experto en matemáticas y ciencias de la computación que desde muy pequeño mostró una gran pasión por la enseñanza.Actualmente cuenta con más de 10 años de experiencia siendo instructor de ciencias y tecnología. Es especialista en Algoritmos, Matemática Discreta, Inteligencia Artificial, Lenguaje Máquina, entre otros temas.Lucas se encuentra investigando en la prestigiosa Universidad Politécnica de Cataluña UPC en Barcelona.A lo largo de su vida, ha dado múltiples conferencias en universidades y organizaciones sobre la enseñanza de las matemáticas.
    Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.
    • language english
    • Training sessions 49
    • duration 14:51:43
    • Release Date 2023/03/18