Get Mastering in Machine Learning with Python – Mindmajix

Machine Learning with Python and its basics that is necessary to master

Machine Learning with Python is a necessity to execute the basic operation related to artificial intelligence. If one intends to know the art of machine learning, then a proper understanding of Python is necessary. It is important to note that it has widespread popularity as a general-purpose programming language. Moreover, it has been adopted in both computing and scientific machine learning. This programming language is popular among many data scientists who are looking forward to building data crunching machines with sophisticated algorithms. However, the best way to learn machine learning is by completing and designing small projects.

Machine Learning with Python can be a bit complex when getting started

It is a widely accepted fact that Python is a powerful and popular programming interpreted language that comes handy in machine learning. Unlike other languages like R, Python is a complete language that can be used for research and development. It is also known as the platform with the assistance of which production systems can be developed. It is interesting to note that python executes a dynamic type system along with automatic memory management that has the ability to support procedural styles and functional programming.

Machine Learning Algorithms Types

Some steps to master the art of Machine Learning with Python

You would be fascinated to know that Python is a multi-paradigm programming language which is also known as an object-oriented programming code. It uses dynamic typing and also a mix of reference counting with the help of machine learning becomes easy. Another important feature of Python lies in the fact that it supports dynamic late binding. That is, it has the ability to bind variable names and methods during the execution of the program. Python has been designed in such a manner that it supports functional programming too. This is why Machine Learning with Python is quite easy when compared to other modern machine learning programs. Here is the list of steps that one should take into account while using Python to master the art of Machine Learning.

Machine Learning with Python with Basic Skills

If you want to learn machine learning with the programming language Python, then you must possess some basic understanding of this language. Due to the widespread popularity as a general language to formulate programs, it is adopted to a great scale in computing and machine learning. However, you need to possess the necessary skills that would come handy if you are looking forward to learning Python.

Conduct a brief overview of the scientific Python packages

It is important to note that beyond Python, there is a host of open source libraries that can be implemented to master practical machine learning. In general, the experts call them as scientific Python libraries which can be put to use while performing simple machine learning tasks. Some of the packages are listed below.

1. Pandas – It is a Python data analysis library which comprises of data frames and structures.
2. Numpy – It is mainly used for its N-dimensional array objects.
3. Scikit-learn – It is a machine learning tool or algorithm that is being used to analyze data and mine data.

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Machine Learning with Python

Cassandra Tutorial – Free Cassandra NoSQL Tutorials for Beginners

This tutorial gives you an overview and talks about the fundamentals of Apache Cassandra.

Why NOSQL and What is NOSQL?

The RDBMS has been the de-facto standard for managing data since it first appeared from IBM in the mid-1980s. The RDBMS really exploded in the 1990s with Oracle, Sybase, Microsoft SQL Server, and other similar databases appearing in the data centers of nearly every enterprise – databases you likely use today.
With the first wave of Web applications, open source RDBMS’s such as MySQL and Postgres emerged and became a standard at many companies that desired alternatives to expensive proprietary databases sold by vendors such as Oracle.
However, it wasn’t long before things began to change, and the application and data center requirements of key Internet players like Amazon, Facebook, and Google began to outgrow the RDBMS. The need for more flexible data models that supported agile development methodologies and the requirements to consume large amounts of fast-incoming data from millions of Web and mobile users around the globe – while maintaining extreme amounts of performance and uptime – necessitated the introduction of a new data management platform.

Enter NoSQL.

Today, with every company utilizing modern Web and mobile applications, the data problems originally encountered by the Internet giants have become common issues for every company, including yours. This means that you and your team of database administrators must realize that it is no longer a question of if you will be deploying and managing NoSQL database systems, but when, and how much of your company’s data will eventually be stored on NoSQL platforms.

Types of NOSQL Databases

There are different types of NoSQL databases, with the primary difference characterized by their underlying data model and method for storing data. The main categories of NoSQL databases are:
Wide Row Store– Also known as wide-column stores, these databases store data in rows and users are able to perform some query operations via column-based access. A wide-row store offers very high performance and a highly scalable architecture. Examples include: Cassandra, HBase, and Google BigTable.
Key/Value– These NoSQL databases are some of the least complex as all of the data within consists of an indexed key and a value. Examples include Amazon DynamoDB, Riak, and Oracle NoSQL database.
Document– Expands on the basic idea of key-value stores where “documents” are more complex, in that they contain data and each document is assigned a unique key, which is used to retrieve the document. These are designed for storing, retrieving, and managing document-oriented information, also known as semi-structured data. Examples include MongoDB and CouchDB.
Graph– Designed for data whose relationships are well represented as a graph structure and has elements that are interconnected; with an undetermined number of relationships between them. Examples include: Neo4J and TitanDB.

What is Cassandra

Cassandra is a fully distributed, masterless database, offering superior scalability and fault tolerance to traditional single master databases. Compared with other popular distributed databases like Riak, HBase, and Voldemort, Cassandra offers a uniquely robust and expressive interface for modeling and querying data. What follows is an overview of several desirable database capabilities, with accompanying discussions of what Cassandra has to offer in each category.

Horizontal Scalability

Horizontal scalability refers to the ability to expand the storage and processing capacity of a database by adding more servers to a database cluster. A traditional single-master database’s storage capacity is limited by the capacity of the server that hosts the master instance. If the data set outgrows this capacity, and a more powerful server isn’t available, the data set must be sharded among multiple independent database instances that know nothing of each other. Your application bears responsibility for knowing to which instance a given piece of data belongs.
Cassandra, on the other hand, is deployed as a cluster of instances that are all aware of each other. From the client application’s standpoint, the cluster is a single entity; the application need not know, nor care, which machine a piece of data belongs to. Instead, data can be read or written to any instance in the cluster, referred to as a node; this node will forward the request to the instance where the data actually belongs.
The result is that Cassandra deployments have an almost limitless capacity to store and process data; when additional capacity is required, more machines can simply be added to the cluster. When new machines join the cluster, Cassandra takes care of rebalancing the existing data so that each node in the expanded cluster has a roughly equal share.

High Availability

The simplest database deployments are run as a single instance on a single server. This sort of configuration is highly vulnerable to interruption: if the server is affected by a hardware failure or network connection outage, the application’s ability to read and write data is completely lost until the server is restored. If the failure is catastrophic, the data on that server might be lost completely.
A master-follower architecture improves this picture a bit. The master instance receives all write operations, and then these operations are replicated to follower instances. The application can read data from the master or any of the follower instances, so a single host becoming unavailable will not prevent the application from continuing to read data. A failure of the master, however, will still prevent the application from performing any write operations, so while this configuration provides high read availability, it doesn’t completely provide high availability.
Cassandra, on the other hand, has no single point of failure for reading or writing data. Each piece of data is replicated to multiple nodes, but none of these nodes holds the authoritative master copy. If a machine becomes unavailable, Cassandra will continue writing data to the other nodes that share data with that machine, and will queue the operations and update the failed node when it rejoins the cluster. This means in a typical configuration, two nodes must fail simultaneously for there to be any application-visible interruption in Cassandra’s availability.
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What is Agile Project Management | Agile Tutorial

What is Agile Project Management?

Agile Project Management is a repetitive process or an approach to look out the work process of a company that will help in managing team work, time-management, planning and improving the work environment, create flexibility, and producing a high-quality product for the high scope of the company betterment. It has the constant changing variables priorities.

Agile’s Rise

Serialized Process- Repeatative approach with tasks broken into small increments.
Planning far in advance– Plan for what we know and we have left sufficient allowance in our plans for what we don’t know.
Lack of Visibility- Team doesn’t realize they are behind schedule.
Project Timeline– Allows the development effort to get feedback from the customer throughout.
Static Requirements– Scope is never closed; Continual reassessment of requirement priorities by the business.

Agile Project Management Framework

Agile Project Mnagement Framework depicts a series of step that will take you initial vision of the product to the final product:
Envision- It determine the product vision and scope the project community  and how the team will work together. It defines the begining of the project like a kick-off meeting.
Speculate- Develop a feature base release milestone and it should function to develop upon the vision. Translates product vision into backlog requirements, which are user stories.
Explore- Delivered tested features in an assured time frame constantly seeking to reduce the risk and the uncertainity of the project. Team starts delivering the work, testing, and accepted in form of stories.
Adapt– Review the delivered results to the current situation and the team performance that is neccessary. Project team constantly, evaluate and make appropriate adaptive actions.
Close– Conclude the project and celebrate. It is closed in an orderly manner. Key learning and lessons are captured, and in the end the celebration of project closures.
Agile is like an Umbrella term which is widely used in different methodologies like:
Scrum– It is a framework for solving complex problems. A recent survey shows that more than 50% of Agile practioner that their team is doing scrum.
Lean– It is also a valuable Agile methodology and so are included in the Agile development umbrella. To maximize customer value while minimizing waste.
Other Methodologies includes ‘Kanban’, ‘Feature Driven Development’, ‘Extreme Programming’, ‘Dynamic Systems Development Method’, ‘Crystal’, and many other.

Agile Lean Framework focues on 7 principles:

Elimanate Waste
Amplify Learning
Decide as late as possible
Deliver as fast as possible
Empower the team
Build integrity in
See the whole, think big, act small, feel fast, and learn rapidly.
As a result, this summerizes the importance of being Lean.

Traditional  Vs  Agile Project Management

Traditional Project Management:
Focus on plans and artifacts.
Response to change via corrective and preventive actions.
Typically up-from planning.
Top-down control.
Scope based delivery.
Contract oriented.
Agile Project Management:
Focus on customer interaction and satisfaction.
Change controlled through adaptive actions.
Progressive elaboration with release and iterative planning.
Self-organizing and cross-functional teams.
Time-boxed delivery.
Customer oriented.

Agile Scrum Framework contributes to 5 values:

Courage– It should have the courage to committ to act to be open
Respect- Expect respect, need to be transperant and respected.
Feedback- Get feedback quickly
Communication– Collaborate to 5 to 9 people not too large.
Simplicity– Simple and sweet that is all and having unneccessary complex processes creates waste and in Agile we focuses in elimanating the waste.
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How to use and Create Date Field in Tableau

Tableau recognizes dates that are contained in your source data and allows you to change the level of detail displayed via an auto-generated hierarchy. It is also possible to rearrange date levels by changing the order of date pills on the row or column shelves.

                                              Diagram of combination filter applied to a bar chart

Discrete and continuous time:

You’ve probably noticed by now that some pills are green and others are blue. Similarly, icons can be in blue or green colors. most beginners believe blue pills and icons denote dimensions while green pills are used to display measures. While this is frequently the case, the truth is more subtle. Blue pills/ icons denote “discrete” fields. Green pills/ icons denote “continuous” fields. Dates can be both discrete and continuous. Below Diagram shows Tableau’s default way of displaying time— as discrete time hierarchy.

You can see that time has been discretely segmented in the time series chart by year. Clicking on the plus sign in the quarter pill would cause the date hierarchy to expand to include months, and panes for each quarter would be exposed. Continuous dates don’t discretely bucket time but will cause a drill down to a lower level of detail. Below Diagram shows a similar time series chart with continuous time being used and the level of detail being month.

The green pill on the column shelf in Below Diagram indicates the level of detail being displayed. Notice that there are no panes in view. Time is continuously displayed as an unbroken line.

                                Discrete time series Diagram

                                          Continuous time series Diagram

Tableau’s date hierarchy:

Time can be expanded to more granular levels simply by clicking on the plus sign within the date pill. Experiment with this and note that you can rearrange time buckets just by changing the order of the pills by repositioning them. It’s also possible to change the level of detail displayed by right-clicking on the date pill. This exposes the menu in below diagram.

                                Diagram of changing the date level of detail

The menu includes two different date sections that start with year. The first group provides discrete date parts. The second group provides continuous date values. Below Diagram was created by changing the date displayed in by altering the quarter pill to display month.

                                Diagram of time series displaying discrete year-month

In Below Diagram note the menu option appears twice the first time it appears is, within the discrete date section of the menu. The second time it is in the continuous date section. Explore the menu option in both the discrete and continuous time portions of the menu. The more menu options provide even more granular options for controlling how date and time are presented in your view.

Rearranging time with Tableau:

There are many different date and time combinations that can be displayed. Below Diagram rearranges time to display weekday first, then year. Each day is a discrete time bucket. You can also add a reference line by pane that displays the average sales value for each weekday across all four years. This is one of the ways you can leverage discrete time to provide additional information.

                              Diagram of Rearranging time and applying a reference line

If your data supports very granular views of data, tableau can display details down to the second. This might be particularly useful if you need to analyze click stream data on a website.

Creating customized date fields in Tableau:

                                       Diagram of Creating a custom date

Tableau’s date hierarchy is always available. Even people consuming reports via tableau reader or server can expand time. When hovering your mouse pointer over an axis you will see a small plus or minus sign appearing. Clicking on those signs expands or contracts the date hierarchy displayed.

Designers with tableau desktop can alter tableau’s default date hierarchy by creating custom date fields and then building unique date hierarchies. Making custom date hierarchies requires three steps:

    1. Create a custom date
    2. Create the date hierarchy.
    3. Use the custom date in your view.

To create a custom date, point at a date field on the dimension shelf and right-click. This will expose a dialog box that provides a means for defining a custom date or time element as you see in below diagram.

Create a custom year date by naming the field “year” and defining the date as a discreet year date part. You can also add another discrete date for month. By dragging the custom month on top of the custom year, you can add a new custom date hierarchy. Below diagram shows the resulting date hierarchy.

You can see the custom hierarchy in below diagram on the dimension shelf. The year and month custom dates are displayed in this time series chart. In this way you can change how tableau expands and contracts the dates used in your visualizations.

Tableau’s date facility encourages explorations of data over different time slices because it is very easy to use and also it doesn’t require any special skill to master.

                                  Custom date hierarchy Diagram

Taming Data with Measure Names and Values:

Sometimes your data isn’t clean and it may not be structured in a way that supports the analysis you need to perform. You might also be looking at a data set for the first time and need to scan it quickly to get a lay of the land. Tableau’s measure names and measure values fields help you with all these tasks.

Click For More Information: How to use Date Field in Tableau

Dynamics Learning: Microsoft Dynamics NAV Overview

Most Organizations having exceptional performances in their past, prefer to take on more opportunities to raise their performances and resort to Microsoft Dynamics NAV. This software looks familiar to MS Office tools like Outlook, Word, Excel, etc to fulfill common responsibilities including Mail Boxes. Various service plans supports organizations to stay complaint without compromising on competitiveness which in turn gives the highest return on investments.

Moreover the capability to upscale the software as per the requirements, gives the organization a greater level of flexibility. Many organizations across the globe have resorted to this application and they hire experts who can help them run the show on this software. In short Microsoft Dynamics helps the organization to evolve on its own terms rather than using generalized software. It helps in the personalization of each and every customer care point.

What is Microsoft Dynamics NAV?

Microsoft Dynamics NAV (formerly Navision) is a global enterprise resource planning (ERP) solution that provides small and mid-size businesses with greater control over financials and can simplify supply chain, manufacturing, and operations. It is quick to implement and easy to use, with the power to support your growth ambition.

What is Microsoft Dynamics NAV used for?

Microsoft Dynamics NAV is an enterprise resource planning (ERP) software suite for midsize organizations. The system offers specialized functionality for manufacturing, distribution, government, retail, and other industries.

What is the meaning of Navision?

Navision software, also referred to as Microsoft Dynamics Nav, is a Microsoft software program designed to work with small and medium-sized enterprises. Navision provides assistance in such enterprise-related areas as customer relationship management, manufacturing and finance.

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What is NAV program?

Microsoft Dynamics NAV originates from Navision, a suite of accounting applications which Microsoft acquired in 2002. Navision originated at PC&C A/S (Personal Computing and Consulting), a company founded in Denmark in 1984.

What Can Microsoft NAV Do for You?

With Microsoft Dynamics NAV, employees can become more effective and the company more competitive. Storing information from across your organization into one centralized database, the system is simple to use and allows your team to work quickly and efficiently.

What projects are included in Online Microsoft Dynamics NAV ?

The projects in this course are based on financial management, payroll management, cost effectiveness and customization of users as per the need of the client and organization.

Microsoft Dynamics NAV learning trends –

Jobs for certified Microsoft Dynamics NAV professionals have been rising and are supposed to be one of the most sought after jobs in futuristic era.
Many global organizations are more and more using this software giving more confidence to new clients who are willing to update from conventional methods of operation to Microsoft Dynamics NAV.

Why to Choose Mindmajix?

Mindmajix is your software and technology training capital for all advanced software modules. It is creating and shaping brilliant minds that are efficient and versatile to scale greater heights in the present technological world. We also offer placements based solely on merit and guarantee a wide span of hands-on training projects with our ongoing developmental processes.

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Microsoft Dynamics NAV Training Material 

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PL/SQL Oracle tutorial, Oracle introduction, PL/SQL basics

Oracle is a relational database technology developed by Oracle.

PLSQL stands for “Procedural Language extensions to SQL”, and is an extension of SQL that is used in Oracle. PLSQL is closely integrated into the SQL language, yet it adds programming constructs that are not native to SQL.

What is Oracle PL SQL and it use?

PL/SQL (Procedural Language/Structured Query Language) is Oracle Corporation’s procedural extension for SQL and the Oracle relational database. … Oracle Corporation usually extends PL/SQL functionality with each successive release of the Oracle Database.

In contrast, PL/SQL tell the database how to do things (procedural). 5.) SQL is used to code queries, DML and DDL statements. PL/SQL is used to code program blocks, triggers, functions, procedures and packages.

Why to attend Mindmajix Online Training ?​

Classes are conducted by Certified Oracle PL/SQLWorking Professionals with 100 % Quality Assurance.

With an experienced Certified practitioner who will teach you the essentials you need to know to kick-start your career on Oracle PL/SQL. Our training make you more productive with your Oracle PL/SQL Online Training. Our training style is entirely hands-on. We will provide access to our desktop screen and will be actively conducting hands-on labs with real-time projects.

What are the objectives and learning outcomes of this course?

Oracle PL/SQL course makes an emphasis on date functions, Create Subqueries and Transaction Control Language. It explicitly adapts SQL statements within its syntax. The course curricula include:

Oracle database environment
Basic SELECT Statement
Ordering the Output
Conditional Retrieval of Data
Pseudo Columns and Functions
Character Functions
Processing Hierarchies

The training explores each topic through the lens of a real-world example application. With plenty of examples, tips, and clear explanations, you’ll master many advanced aspects of Oracle PL/SQL.

Click for more information: MySQL Procedural Language

Get The Best Oracle 12c DBA Certification Training

MindMajix is creating and shaping brilliant minds that are efficient and versatile to scale greater heights in the present technological world. We also offer placements based solely on merit and guarantee a wide span of hands-on training projects with our ongoing developmental processes.

The data entrusted to Oracle is stored in a series of data files on disk drives of the computer that is running the Oracle RDBMS. It would be nice if the simple categorization structure described previously covered all possible DBA job descriptions. However, there are many nuances in the roles and responsibilities that should be considered in light of your talents and the “culture” found in your organization. If nothing else, studying other people’s work environments is an interesting pastime. When you are a consultant, you need something to get you through certain routine assignments.

An in-depth knowledge of an Oracle DBA 12c / 11g project ensures all the critical components are well-covered. With this knowledge, you can increase your visibility and enhance your efficiency in drawing real connections among different components of DBA.

Oracle DBA 12c (Oracle Database Administration) is responsible for the design, implementation, support and maintenance of databases in everyday enterprises. Oracle DBA role ensures security, performance and efficient availability of data to users and customers.

Dropping Tablespaces in Oracle DBA:

You can drop a tablespace and its contents (the segments contained in the tablespace) from the database, if the tablespace and its contents are no longer required. You must have the drop tablespace system privilege to drop a tablespace.


Once a tablespace has been dropped, the data in the tablespace is not recoverable. Therefore, make sure that all data contained in a tablespace to be dropped will not be required in the future. Also, immediately before and after dropping a tablespace from a database, back up the database completely. This is strongly recommended so that you can recover the database if you mistakenly drop a tablespace, or if the database experiences a problem in the future after the tablespace has been dropped.

When you drop a tablespace, the file pointers in the control file of the associated database are removed. You can optionally direct oracle database to delete the operating system files (datafiles) that constituted the dropped tablespace. If you do not direct the database to delete the datafiles at the same time that it deletes the tablespace, you must later use the appropriate commands of your operating system to delete them.

Learn more about this kind of interesting topics visit: Oracle DBA