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Machine Learning with Python today

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Overview

  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Impress interviewers by showing an understanding of the data science field
  • Learn how to pre-process data
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don't teach!)
  • Start coding in Python and learn how to use it for statistical analysis
  • Perform linear and logistic regressions in Python
  • Carry out cluster and factor analysis
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Apply your skills to real-life business cases
  • Use state-of-the-art Deep Learning frameworks such as Google's TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Unfold the power of deep neural networks
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations

Who this course is for?

You should take this course if you want to become a Data Scientist or if you want to learn about the field
This course is for you if you want a great career
The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills

Course Curriculum

  1. Machine Learning with Python
    1. Part 1: Introduction
    2. The Field of Data Science - The Various Data Science Disciplines
    3. The Field of Data Science - Connecting the Data Science Disciplines
    4. The Field of Data Science - The Benefits of Each Discipline
    5. The Field of Data Science - Popular Data Science Techniques
    6. The Field of Data Science - Popular Data Science Tools
    7. The Field of Data Science - Careers in Data Science
    8. The Field of Data Science - Debunking Common Misconceptions
    9. Part 2: Probability
    10. Probability - Combinatorics
    11. Probability - Bayesian Inference
    12. Probability - Distributions
    13. Probability - Probability in Other Fields
    14. Part 3: Statistics
    15. Statistics - Descriptive Statistics
    16. Statistics - Practical Example: Descriptive Statistics
    17. Statistics - Inferential Statistics Fundamentals
    18. Statistics - Inferential Statistics: Confidence Intervals
    19. Statistics - Practical Example: Inferential Statistics
    20. Statistics - Hypothesis Testing
    21. Statistics - Practical Example: Hypothesis Testing
    22. Part 4: Introduction to Python
    23. Python - Variables and Data Types
    24. Python - Basic Python Syntax
    25. Python - Other Python Operators
    26. Python - Conditional Statements
    27. Python - Python Functions
    28. Python - Sequences
    29. Python - Iterations
    30. Python - Advanced Python Tools
    31. Part 5: Advanced Statistical Methods in Python
    32. Advanced Statistical Methods - Linear Regression with StatsModels
    33. Advanced Statistical Methods - Multiple Linear Regression with StatsModels
    34. Advanced Statistical Methods - Linear Regression with sklearn
    35. Advanced Statistical Methods - Practical Example: Linear Regression
    36. Advanced Statistical Methods - Logistic Regression
    37. Advanced Statistical Methods - Cluster Analysis
    38. Advanced Statistical Methods - K-Means Clustering
    39. Advanced Statistical Methods - Other Types of Clustering
    40. Part 6: Mathematics
    41. Part 7: Deep Learning
    42. Deep Learning - Introduction to Neural Networks
    43. Deep Learning - How to Build a Neural Network from Scratch with NumPy
    44. Deep Learning - TensorFlow 2.0: Introduction
    45. Deep Learning - Digging Deeper into NNs: Introducing Deep Neural Networks
    46. Deep Learning - Overfitting
    47. Deep Learning - Initialization
    48. Deep Learning - Digging into Gradient Descent and Learning Rate Schedules
    49. Deep Learning - Preprocessing
    50. Deep Learning - Classifying on the MNIST Dataset
    51. Deep Learning - Business Case Example
    52. Deep Learning - Conclusion
    53. Appendix: Deep Learning - TensorFlow 1: Introduction
    54. Appendix: Deep Learning - TensorFlow 1: Classifying on the MNIST Dataset
    55. Appendix: Deep Learning - TensorFlow 1: Business Case
    56. Software Integration
    57. Case Study - What's Next in the Course?
    58. Case Study - Preprocessing the 'Absenteeism_data'
    59. Case Study - Applying Machine Learning to Create the 'absenteeism_module'
    60. Case Study - Loading the 'absenteeism_module'
    61. Case Study - Analyzing the Predicted Outputs in Tableau
    62. Appendix - Additional Python Tools
    63. Appendix - pandas Fundamentals

Exam & Certification

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These web-based courses are intended for any individual who needs to become familiar with the most recent advanced abilities. We give courses in the fields of information science, web improvement, application advancement, and significantly more. Intended for all experts, these courses help students and novices, as well as experienced developers, specialists, administrators, and chiefs. The educational program is planned by eminent industry specialists and course counselors.

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FAQ

What is SpeedoLearn?

SpeedoLearn is a platform where students can take internet based courses. Master popular abilities on your schedule. you can investigate and acquire popular abilities on your schedule. This course made by industry specialists and top experts.

For whom these courses are meant for?

These web-based courses are intended for any individual who needs to become familiar with the most recent advanced abilities. We give courses in the fields of information science, web improvement, application advancement, and significantly more. Intended for all experts, these courses help students and novices, as well as experienced developers, specialists, administrators, and chiefs. The educational program is planned by eminent industry specialists and course counselors.

How can I sign up?

Fill up the enquiry form and we will contact you in 24 hours.

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