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  Best Python libraries for Machine Learning Machine Learning, as the name suggests, is the science of programming a computer by which they are able to learn from different kinds of data. A more general definition given by Arthur Samuel is – “Machine Learning is the field of study that gives computers the ability to learn without being explicitly programmed.” They are typically used to solve various types of life problems.  In the older days, people used to perform Machine Learning tasks by manually coding all the algorithms and mathematical and statistical formulas. This made the processing time-consuming, tedious, and inefficient. But in the modern days, it is become very much easy and efficient compared to the olden days by various Python libraries, frameworks, and modules. Today, Python is one of the most popular programming languages for this task and it has replaced many languages in the industry, one of the reasons is its vast collection of libraries. Python libraries that used

Machine Learning – Applications   Introduction Machine learning is one of the most exciting technologies that one would have ever come across. As it is evident from the name, it gives the computer that which makes it more similar to humans: The ability to learn. Machine learning is actively being used today, perhaps in many more places than one would expect. We probably use a learning algorithm dozens of times without even knowing it. Applications of Machine Learning include: Web Search Engine:  One of the reasons why search engines like google, bing, etc work so well is because the system has learned how to rank pages through a complex learning algorithm. Photo tagging Applications:  Be it Facebook or any other photo tagging application, the ability to tag friends makes it even more happening. It is all possible because of a face recognition algorithm that runs behind the application. Spam Detector:  Our mail agent like Gmail or Hotmail does a lot of hard work for us in classifying th

  Machine Learning: What is it really? Well, Machine Learning is a subfield of Artificial Intelligence that evolved from Pattern Recognition and Computational Learning theory. Arthur Lee Samuel defines Machine Learning as a Field of study that gives computers the ability to learn without being explicitly programmed. So, basically, the field of Computer Science and Artificial intelligence that “learns” from data without human intervention. But this view has a flaw. As a result of this perception, whenever the word Machine Learning is thrown around, people usually think of “A.I.” and “Neural Networks that can mimic Human brains ( as of now, that is not possible)”, Self Driving Cars and what not. But Machine Learning is far beyond that. Below we uncover some expected and some generally not expected facets of Modern Computing where Machine Learning is in action. Machine Learning: The Expected We’ll start with some places where you might expect Machine Learning to play a part. Speech Re

   Introduction to Data in Machine Learning DATA:  It can be any unprocessed fact, value, text, sound, or picture that is not being interpreted and analyzed. Data is the most important part of all Data Analytics , Machine Learning, Artificial Intelligence. Without data, we can’t train any model and all modern research and automation will go in vain. Big Enterprises are spending lots of money just to gather as much certain data as possible. Example:  Why did Facebook acquire WhatsApp by paying a huge price of $19 billion? The answer is very simple and logical – it is to have access to the users’ information that Facebook may not have but WhatsApp will have. This information of their users is of paramount importance to Facebook as it will facilitate the task of improvement in their services. INFORMATION:   Data that has been interpreted and manipulated and has now some meaningful inference for the users. KNOWLEDGE:  Combination of inferred information, experiences, learning, and insigh

  Classification of Machine Learning Machine learning implementations are classified into three major categories, depending on the nature of the learning “signal” or “response” available to a learning system which is as follows:-    Supervised learning:  When an algorithm learns from example data and associated target responses that can consist of numeric values or string labels, such as classes or tags, in order to later predict the correct response when posed with new examples that comes under the category of Supervised learning. This approach is indeed similar to human learning under the supervision of a teacher. The teacher provides good examples for the student to memorize, and the student then derives general rules from these specific examples. Unsupervised learning:  Whereas when an algorithm learns from plain examples without any associated response, leaving to the algorithm to determine the data patterns on its own. This type of algorithm tends to restructure the data into so

Digital Marketing Strategies Marketing through online mediums allows you to have more granular control when it comes to targeting users. Having a more targeted approach generally results in a much higher conversion rate and lower acquisition costs. Businesses that use online marketing and make an effort to resonate with their target market see noticeable results. Traditional Marketing Strategies As a leading Perth digital agency, PWD is able to offer clients both traditional and digital marketing services. PWD assists a wide range of Australian businesses with everything from TV advertising and radio, to billboard advertising and print media   Web Design SEO Services Google Ads Social media marketing E-commerce solutions Branding (logo, slogan, etc.) LinkedIn outreach campaigns Display advertising Advanced data analytics Website Development Radio and TV Advertising

  How We Create Hard-Hitting Marketing Campaigns Our expert digital marketing consultants create tailored digital strategies that will set your business apart from the competition. To get started, we’ll introduce you to the team and process to know what to expect. Next, we’ll assess your needs based on the type of product or service you provide and the industry you’re in. Our team will analyze data about your current and ideal customers and what other companies in your space are doing. Once we have a good idea of your business, industry, and preferences, our team will develop digital solutions that specific to your needs. From this point, we can adjust your marketing strategy as we continue to analyze data and receive feedback from you. Throughout our agency, we have an incredible range and depth of skills. Our marketing teams work alongside your company and aim to serve rather than taking over. Once your company and our digital marketing specialists are happy with how everything looks

  What is Digital Marketing? One can best describe digital marketing by comparing it to traditional marketing, which utilizes mediums like newspaper ads and billboards. Each digital marketing channel gives businesses another chance to put themselves in front of the right users and increase traffic to their sites. For example, effective SEO strategies will help your entire site or a specific web page rank more highly on search engine results, increasing your company’s visibility. In contrast, digital marketing uses a variety of digital outlets such as: Google and other search engines Search Engine Optimisation PPC (Pay-per-click) advertising Websites social media advertising (Facebook, Instagram, etc) Email marketing Mobile marketing (apps) Content marketing and digital PR (blog posts, LinkedIn articles, etc.) Lead magnets (free digital products in exchange for contact info) Conversion Rate Optimisation (CRO)

Best digital marketing in Perth Introduction Your introduction into the brave new world of the digital space will be custom-tailored to your business needs requirements. You will be introduced to the crew who will be handling your project, from inception to the launch into the market. Assess It will be our job to not only know your customers but how they engage with the core products and  brand relationships . From here we break down what we research, to identify the core elements needed to engage the customer. Create It’s imperative that the design of your vessel is done right from the start. Its shape, level of focus, and attention to detail are crucial for a prosperous, lucrative, and extended journey. We will always present concepts and suggestions as per the requirement, but we truly believe this process should be a collaborative one between the creative crew of the PWD and the client. The final form will dictate its progression into the  development  and manufacturing of your new

  Queue in Data Structure The queue data structure is linear. It follows the FIFO approach i.e. First In First Out or Last In Last Out. In the queue , the order of insertion is the same as the order of deletion of elements because of the FIFO approach. Queues are mostly used whenever there is a single resource and multiple users want to use that resource. For example, in threads and CPU scheduling algorithms. A data structure queue is analogous to a queue in real life. For example, people waiting in a queue to buy movie tickets. Representation of a Queue Just like a stack, the queue is also an abstract data type but it follows the FIFO approach. In the queue , we always remove the least recently added element. A queue is open at both ends, unlike a stack. Thus we perform deletion and insertion operations at two different ends in a queue .The two ends of the queue are the  Front  and  Rear  respectively. Front points to the index of the queue from where we can delete an element. Rear p

                Different between Linear search vs Binary search Linear search Binary search It follows a sequential approach. This follows a divide and conquer approach. It works well on unsorted data. To apply binary search, data has to be sorted. Its worst-case time complexity is O(n). Its worst-case time complexity is O(log n) It is slower in comparison to binary search. It is more efficient than linear search. In linear search, we compare an element with every other element. In binary search, we don’t compare an element with all other elements. We leave a few comparisons. We prefer linear search only for small-sized data. It is preferred for large-sized data. We can implement linear search on all linear data structures like arrays and linked lists.  We can implement binary search only on those data structures that permit 2-way traversal.

  Binary Search in Data Structure There are various ways to search a particular element from a given list. One of them is Binary search . When there exists so much data everywhere, it is very necessary to have a good searching method to search for the particular data in lesser time. Binary search works faster than linear search. It is one of the fastest searching algorithms. What is Binary Search? It is a searching technique. It is based upon Divide and conquer strategy. Binary search is applicable only on sorted data. It takes O(log n) time for completion. It divides the given array into halves and then checks the middle element. If the middle element is smaller than the element to be searched, the algorithm selects the second half of the array and discards the first half. Thus, at every step, the binary search algorithm keeps on discarding half of the array based on the value of the middle element. This process continues until the array becomes of the size 1 or 2 and the algorithm