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Python fundamental tutorials:
Data structure, function creation, control flow, Numpy, Pandas, visualization using matplotlib.
Python statistics:
Doing and discovering statistics using Python programming.
Python functions handling calculating the density, cumulative probability, quantile and random number generation for different statistical distributions: Normal distribution, t distribution, gamma distribution, chi-square distribution, F distribution, beta distribution, Hypothesis testing, etc.
Linear regression and Generalized linear models using Python programming.
ANOVA, factor analysis using Python programming.
Clustering model using Python programming.
Python machine learning:
tensorflow, keras, scikit-learn.
We provide effective and economically affordable online training courses for R and Python, click here for more details and course registration ! List comprehension is a concise way to create a list in Python. It is usually a composition of an expression with a for loop statement in the bracket. Read more…
We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! Although a numerical list can be created manually by filling each element within square brackets in Python, very often will the analyst use some type of ready functions. For Read more…
We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! Looping in Python provides a feasible way to deal with each element of an object for particular operations using just a single block of statements. A for loop handling Read more…
We provide effective and economically affordable training courses for R and Python, click here for more details and course registration ! String variables in Python are data objects encapsulated in double or single quotes. For example we can create a string variable ‘msg’ and print it out in the following Read more…
We provide effective and economically affordable training courses for R and Python, Click here for more details and course registration ! When a list is created in Python, the order of its element contained can be sorted in alphabetical order later. There are mainly two functions for sorting a list Read more…
Dictionary is a data structure type in Python. One reason for why Python is so popular among programmers is that dictionary provides an useful and effective way to store key-value pairs information. When functions in Python carry out some tasks, it can return required information to a dictionary.
The exponential distribution is modeling the probability distribution of the random time until next event occur in a Poisson event process. A Poisson event process has a constant occurring rate during an interval. Exponential distribution is a particular case of the gamma distribution when the shape parameter (alpha) equals 1.
The elements of a list can be added or removed after it has been created.
To add new elements at the end of a list, Py
Python uses class for object-oriented programming. A class represents the general behavior or information that the programmer or data analyst focuses on. When a class is created, particular objects belonging to this class can be created. This process is called instantiation. Class contains attributes, methods, or functions for general purpose. Attributes for instances can be modified by directly assigning new values, or by using methods defined in a class.
Normal distribution is describing random variables with bell-shaped probability density functions. Normal distribution is widely used in data science because large sample random variates have a mean value which follows approximate normal distribution if variates are independently drawn from any distributions. The probability density function for normal distribution is determined by two parameters: mean(miu) and standard deviation(sigma).