Machine Learning A-Z™: Hands-On Python & R in Data Science Free Download

Description

Free Download Machine Learning A-Z™: Hands-On Python & R in Data Science, with this course you will have the option to Machine Learning , Python, Advanced Data Visualization, R Programming, Linear Regression, Decision Trees, NumPy, Pandas. It contains 151 recordings. Remember that numerous understudies are tried out this course Machine Learning A-Z™: Hands-On Python & R in Data Science, so don't hold on to download it presently, it's totally free. You can start learning Machine Learning A-Z™: Hands-On Python & R in Data Science by clicking the download link below.

Before you can start learning from this course explained in English (US) you need to have Basic Knowledge of Python.

Machine Learning A-Z™: Hands-On Python & R in Data Science is targeting for people that have interset in Anyone who is interested in Machine Learning and Data Science, Students who have at least high school knowledge in math and who want to start learning Machine Learning, This course is also for any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning, Anyone who want to start a career in Data Science and Machine Learning or anyone who wants to become a Data Scientist, Any data analysts who want to level up in Machine Learning, People who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets, Any students in college who want to start a career in Data Science, Any data analysts who want to level up in Machine Learning.

Finally you will learn how to Learn the use of Python for Data Science and Machine Learning, Learn the use of Advanced R for Data Science and Machine Learning, Advance Data Visualization, Charts, Statistics, Statistics, Linear Regression, Logistic Regression, Poisson Regression, Time Series, Linear Regression, Decision tree, Data Manipulation,, In-depth Supervised and Unsupervised Mahine Learning, TensorFlow, Algorithms, Artificial Neural Networks, Clustering, In-depth jupyter, NumPy, Pandas, Matplotlib, Scikit learn, SVM, Random Forest,, Have a great intuition of a lot of Machine Learning models, Make robust Machine Learning models.

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