#arithmetic progression formula class 10

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The Integrated Program in Management Aptitude Test (IPMAT) is a highly competitive exam conducted by IIM Indore and IIM Rohtak for admission to their five-year Integrated Program in Management (IPM). Cracking the IPMAT requires dedication, strategic planning, and expert guidance.

If you are aiming for success, this 6-month study plan will help you prepare effectively. Whether you prefer IPMAT coaching online in Delhi or offline IPMAT classes near you in Delhi, following a structured approach will increase your chances of scoring high.

Understanding the IPMAT Exam

Before starting your preparation, it’s crucial to understand the exam pattern and syllabus.

IPMAT Exam Structure

The IPMAT exam consists of two sections:

Quantitative Ability (QA) — Includes questions from Arithmetic, Algebra, Geometry, Data Interpretation, and Logical Reasoning.

Verbal Ability (VA) — Tests your Reading Comprehension, Grammar, Vocabulary, and Sentence Correction skills.

IIM Indore includes Short-Answer Questions (SAQs) in QA, while IIM Rohtak focuses on Multiple-Choice Questions (MCQs).

6-Month Study Plan to Ace IPMAT

A well-structured study plan ensures you cover all topics systematically. Here’s a month-wise breakdown of your preparation.

Months 1–2: Build a Strong Foundation

Understand the syllabus — Go through the complete syllabus and exam pattern. Master the basics — Focus on Arithmetic, Algebra, and Grammar. Improve vocabulary — Learn 10 new words daily and practice their usage. Join a structured coaching program — Consider enrolling in the best coaching for IPMAT in Delhi or an IPMAT online course for expert guidance.

Recommended Study Hours: 3–4 hours daily

Months 3–4: Practice & Speed Enhancement

Attempt topic-wise tests — Start solving sectional mock tests for QA and VA. Improve calculation speed — Practice mental math and shortcut techniques. Strengthen reading skills — Read newspapers, articles, and editorials daily. Enroll in IPMAT online coaching — If you prefer flexible learning, consider IPMAT coaching online for expert-led classes.

Recommended Study Hours: 4–5 hours daily

Months 5–6: Mock Tests & Final Preparation

Solve full-length mock tests — Take at least 2–3 full-length tests per week. Analyze performance — Review mistakes and focus on weak areas. Work on time management — Practice solving questions within time limits. Revise key concepts — Go through formula sheets, grammar rules, and vocabulary lists.

Recommended Study Hours: 5–6 hours daily

Why Join Genius Tutorials IPMAT Coaching for Better Results?

Many students struggle with self-study due to lack of structured guidance. Enrolling in a Genius tutorials IPMAT preparation coaching in Delhi program offers expert mentorship, doubt-solving sessions, and practice materials.

Top Benefits of IPMAT Coaching:

Expert Guidance — Learn from experienced mentors who understand IPMAT strategies. Regular Mock Tests — Evaluate your progress and improve weak areas. Concept Clarity — Get detailed explanations for difficult topics. Personalized Study Plans — Tailored strategies for different learning speeds.

If you are looking for IPMAT coaching near you in Delhi, Genius Tutorials offers comprehensive courses to help you succeed.

Best Online Coaching for IPMAT — Study from Anywhere!

For students who prefer flexible learning, IPMAT online coaching is a great option. Online courses provide:

Live interactive classes — Learn from experts in real-time. Recorded sessions — Revisit lessons anytime for revision. Doubt-solving forums — Get answers to queries instantly. Structured study plans — Follow a step-by-step curriculum.

Genius Tutorials offers the best online coaching for IPMAT, helping students prepare from home with top-notch study materials and expert guidance.

Final Tips to Crack the IPMAT Exam

Stay consistent — Follow the study plan without skipping topics. Manage time wisely — Divide study hours between QA and VA equally. Stay updated — Read newspapers and articles daily for verbal ability improvement. Take care of health — Eat well, exercise, and get enough sleep for better focus.

By following this 6-month strategy, you can boost your confidence and maximize your chances of securing a seat at IIM Indore or IIM Rohtak.

Looking for the best coaching for IPMAT in Delhi? Join Genius Tutorials, Delhi, today! Enroll Now & Start Your IPMAT Journey!

Originally published at https://www.geniustut.com on February 21, 2025.

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Class 9 Math Annual Exam with Model 3

Class 9 Math Annual Exam with Model 3

  Class 9 math exam preparation guide,last minute math exam tips for Class 9,Class 9 math practice questions and solutions,model 3 math prep for Class 9 exam,effective study techniques for Class 9 math exam Math Time: 3                              Hours Class: 9                     Total Marks: 100 Section A: Objective (25 Marks) Multiple Choice Questions: (Write the correct answer on the answer sheet) 1 × 15 = 15 1. a, ar, ar², ar³ is which type of sequence? (a) Geometric (b) Arithmetic (c) Infinite (d) Constant 2. If 7x + 2, 5x + 12, 2x - 1 form an arithmetic progression, what is the value of x? (a) -23 (b) 23 (c) ±23 (d) 21 3. What is the 15th term of the sequence 4 + 8 + 16 + ........? (a) 65536 (b) 131072 (c) 146384 (d) 32768 4. logb n , what is the argument? (a) k (b) n (c) b (d) log 5. What is the base of lnx? (a) e (b) 10 (c) x (d) y 6. What is logbAx? (a) x (b) A (c) b (d) xlogbA 7. If the sum and difference of the digits of a two-digit number are 10 and 4 respectively, what is the number? (a) 47 (b) 27 (c) 37 (d) 57 8. Which point is on the x-axis? (a) (2, 0) (b) (-3, 5) (c) (0, 3) (d) (-2, -2) 9. For θ = 45° - i. sin2 θ + tan2 θ = ii. sin2 θ + cos2 θ = iii. 1 - sin2 θ = Which of the following is correct? (a) i and ii (b) i and iii (c) ii and iii (d) i, ii, and iii 10. Based on the following information, answer questions 10 and 11: In right-angled triangle ABC, ∠C = β, ∠B = α, AB = 7, BC = 25 cm, and AC = 24 cm. What is the length of the side opposite to angle β? (a) 7

(b) 24 (c) 25 (d) 6 11. For which of the following angles is the length of the adjacent side 24 cm? (a) α (b) β (c) �� + β (d) α - β 12. In the first quadrant, how are all trigonometric ratios? (a) Positive (b) Negative (c) 0 (d) Even 13. What is cos 150°? (a) (b) (c) - (d) - 14. How many types of data are there? (a) 2 (b) 3 (c) 4 (d) 5 Class 9 Math Annual Exam with Model 2 15. If ∑fi|xi - Mo| = 216.92 and n = 20, what is the mean deviation calculated from the median? (a) 8×85 (approximately) (b) 10×85 (approximately) (c) 9×85 (approximately) (d) 7×85 (approximately) 16. Write the condition for a, b, c to be in a geometric progression. 17. What is the sum of the first n natural numbers? 18. What is log₂ 16? 19. Write the formula for logb () 20. What is the discriminant of the equation ax² + bx + c = 0? 21. What is the meaning of the word 'Metron'? 22. In the second quadrant, what is the sign of cos θ? 23. What is cot(90° - θ)? 24. What is the range typically represented by? 25. What is the relationship between the mean deviation M.D and the range R for two unequal data sets? 1. Answer the following questions: 2 × 13 = 26 (a) If the third term and fifth term of an arithmetic progression are -12 and 26, respectively, find the first term and common difference. (b) For the series 2 + 4 + 6 + 8 + ..., if the sum of the first n terms is 2550, find the value of n. (c) Find the general term of the arithmetic progression 5, 12, 19, 26, ... (d) If log₅ x = 3, what is the value of x? (e) At a 10% compound interest rate, in how many years will the principal triple? (f) Solve the system of equations using substitution method: 2x + 3y = 32 11y - 9x = 3 (g) Solve the equation 3x² - 2x - 1 = 0 using the quadratic formula. (h) If 12 cot θ = 7, find the value of cos θ. (i) From a point 15 meters away from the base of a tower, the angle of elevation to the top of the tower is 30°. Find the height of the tower. (j) Convert radians to degrees. (k) For the angle θ = ∠XOP in standard position, find the trigonometric ratios for the point A(-4, -3) on the terminal arm. (l) Find the range of the data set: 7, 5, 12, -5, 0, 10. (m) Find the cumulative frequency distribution for the given data: x 60 61 62 63 64 65 66 67 f 2 0 15 30 25 12 11 5 Answer the following descriptive questions (based on the visual context):                                       7 × 7 = 49 2. Consider the following two geometric progressions: (i) x + 1, x + 5, x + 10, ....... (ii) 2 - 4 + 8 - 16 + .... (a) Find the value of x in the first geometric progression x + 1, x + 5, x + 10, ....... (3 marks) (b) Which term of the second geometric progression 2 - 4 + 8 - 16 + ..... is equal to 256? (4 marks) 3. In Arup's school hall, there are 30 rows of benches. The first, second, and third rows have seats in the following quantities: (k + 12), (3k + 10), and (7k + 4) respectively. (a) Find the value of k if the number of seats forms an arithmetic progression. (2 marks) (b) How many seats are there in the last row? (2 marks) (c) Find the total number of seats in the hall. (3 marks) 4. Given that: A = B = , and C = (a) If A = 128, find the value of p. (3 marks) (b) Prove that B ÷ C = . (4 marks) 5. An earthquake is felt in two locations in Bangladesh, Sylhet and Chittagong, on the same day. The magnitude of the earthquake in Sylhet is 6.5, and the earthquake in Chittagong is 17 times stronger. The magnitude of the earthquake in India, which is located near Bangladesh, is 7.1. (a) Find the magnitude of the earthquake in Chittagong. (3 marks) (b) Compare the intensity of the earthquakes in Sylhet and India, and determine which place has a higher risk. (4 marks) 6. Setu's mother bought 25 ducklings and 30 chicks for 5000 taka. If she had bought 20 ducklings and 40 chicks at the same rate, she would have spent 500 taka less. (a) What is the cost of one duckling and one chick? (4 marks) (b) After some time, if each duck is sold for 250 taka and each chicken for 160 taka, what will be her total profit? (3 marks) 7. Samiya bought 4 pens and 2 notebooks for 100 taka from a shop. Lamiya bought 2 pens and 3 notebooks for 110 taka from the same shop at the same price. (a) Form the system of equations from the given information and determine its nature. (3 marks) (b) Find the price of each notebook and pen. (4 marks) 8. Roni and Tahmid were walking along the riverbank when they saw the top of a 100-meter tall tree on the opposite bank. The angle of elevation to the top of the tree from their position was 60°. Later, Tahmid moved back a little and saw that the angle of elevation from his new position was 45°. (a) Calculate the distance from Roni and Tahmid to the opposite bank of the river. (3 marks) (b) How much further back did Tahmid move from Roni? (4 marks) 9. A car travels from Dhaka to Khulna. The rear wheel of the car rotates 12 times per second, and the radius of the wheel is 0.5 meters. The distance from Dhaka to Khulna subtends an angle of 2° at the center of the Earth. (a) How far will the car travel in one full rotation of the wheel? (2 marks) (b) Calculate the speed of the car. (2 marks) (c) How long will it take the car to reach Khulna from Dhaka? (3 marks) 10. The frequency distribution table for the mathematics marks of 125 students of Class 9 is given below: Marks Obtained 10 - 20 20 - 30 30 - 40 40 - 50 50 - 60 60 - 70 Number of Students 10 17 30 40 20 8 (a) What is the average mark of the students in Class 9 in mathematics? (3 marks) (b) Using the assumed mean method or direct method, calculate the deviation from the mean. (4 marks) 11. The following is the frequency distribution table for the number of absences of 40 students in a class last month: Absence Days 1 - 4 5 - 8 9 - 12 13 - 16 17 - 20 Number of Students 5 11 7 2 1 (a) What is the range of the first 12 prime numbers? (2 marks) (b) How many students attended the class every day last month? (2 marks) (c) Calculate the range from the frequency distribution table. (3 marks) Read the full article

[mathswithnarendrasir]

Arithmetic Progression #arithmeticprogression #ap #maths #mathswithnarendrasir

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Maths Class 10 Chapter 5 Arithmetic Progressions : Important Formulas | ...

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CBSE Class 10 Syllabus has been designed to help students gain a deeper understanding of the subject matter.

[ncertsolutionsmath]

NCERT Solutions for Class 10 Maths PDF Download

NCERT Solutions for Class 10 Maths for all the activities from Chapters 1 to 15 are given here. These solutions are curated by our master personnel to help understudies in their board test arrangements. Understudies searching for the NCERT Solutions for Class 10 Maths can download all part shrewd pdf to locate a superior way to deal with take care of the issues. 

The responses to the inquiries present in the NCERT books are without a doubt the best examination material an understudy can get hold of. These CBSE NCERT Solutions of Class 10 Maths will likewise assist understudies with building a more profound comprehension of ideas canvassed in Class 10 Maths course reading. Rehearsing the course reading addresses will assist understudies with examining their degree of readiness and the information on ideas. The solutions to these inquiries present in the books can assist understudies with clearing their questions rapidly.

NCERT Solutions for Class 10 Maths Chapters and Exercises NCERT Solutions for Class 10 Maths Chapter 1 Real Numbers In Chapter 1 of Class 10, students will explore real numbers and irrational numbers. The chapter starts with the Euclid’s Division Lemma which states that “Given positive integers a and b, there exist unique integers q and r satisfying a = bq + r, 0=r<b”. The Euclid’s Division algorithm is based on this lemma and is used to calculate the HCF of two positive integers. Then, the Fundamental Theorem of Arithmetic is defined which is used to find the LCM and HCF of two positive integers. After that, the concept of an irrational number, a rational number and decimal expansion of rational numbers are explained with the help of theorem.

NCERT Solutions for Class 10 Maths Chapter 2 Polynomials In Polynomials, the chapter begins with the definition of degree of the polynomial, linear polynomial, quadratic polynomial and cubic polynomial. This chapter has a total of 4 exercises including an optional exercise. Exercise 2.1 includes the questions on finding the number of zeroes through a graph. It requires the understanding of Geometrical Meaning of the Zeroes of a Polynomial. Exercise 2.2 is based on the Relationship between Zeroes and Coefficients of a Polynomial where students have to find the zeros of a quadratic polynomial and in some of the questions they have to find the quadratic polynomial. In Exercise 2.3, the concept of division algorithm is defined and students will find the questions related to it. The optional exercise, 2.4 consists of the questions from all the concepts of Chapter 2.

NCERT Solutions for Class 10 Maths Chapter 3 Pair of Linear Equations in Two Variables This chapter explains the concept of Pair of Linear Equations in Two Variables. This chapter has a total of 7 exercises, and in these exercises, different methods of solving the pair of linear equations are described. Exercise 3.1 describes how to represent a situation algebraically and graphically. Exercise 3.2 explains the methods of solving the pair of the linear equation through Graphical Method. Exercises 3.3, 3.4, 3.5 and 3.6 describe the Algebraic Method, Elimination Method, Cross-Multiplication Method, Substitution Method, respectively. Exercise 3.7 is an optional exercise which contains all types of questions. Students must practise these exercises to master the method of solving the linear equations.

NCERT Solutions for Class 10 Maths Chapter 4 Quadratic Equations In this chapter, students will get to know the standard form of writing a quadratic equation. The chapter goes on to explain the method of solving the quadratic equation through the factorization method and completing the square method. The chapter ends with the topic on finding the nature of roots which states that, a quadratic equation ax² + bx + c = 0 has

Two distinct real roots, if b² – 4ac > 0 Two equal roots, if b² – 4ac = 0 No real roots, if b² – 4ac < 0

NCERT Solutions for Class 10 Maths Chapter 5 Arithmetic Progressions This chapter introduces students to a new topic that is Arithmetic Progression, i.e. AP. The chapter constitutes a total of 4 exercises. In Exercise 5.1, students will find the questions related to representing a situation in the form of AP, finding the first term and difference of an AP, finding out whether a series is AP or not. Exercise 5.2 includes the questions on finding out the nth term of an AP by using the following formula; an = a + (n-1) d

The next exercise i.e., 5.3, contains the questions on finding the sum of first n terms of an AP. The last exercise includes higher-level questions based on AP to enhance students’ analytical and problem-solving skills.

Source: https://ncertsolutionsmath.news.blog/2021/02/07/ncert-solutions-for-class-10-maths-pdf-download/

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Watch Our Live Session Today At 5:00 PM On Topic -  |Arithmetic progressions L - 5 | Sum of first n terms of an AP - Class 10 CBSE | Empower Tutorials|-https://bit.ly/3iktmHd.............

****Arithmetic Progression/Tricks/Important Questions/Formula/Solution | Sum of First n Terms of an AP | CBSE Class 10 Maths | NCERT Solutions |CBSE Class 10 of NCERT Maths Books.............

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A Convolutional Neural Network with K Nearest Neighbor for Image Classification

Image classification forms the basis for computer vision which is a trending sub-field in Machine Learning. The Convolutional Neural Network (ConvNet) has recently achieved great success in many computer vision tasks. The common architecture of ConvNets contains many layers to recurrently extract suitable image features and feed them to the softmax function for classification which often displays low prediction performance. In this paper, we propose the use of K-Nearest Neighbor as classifier for the ConvNets and also introduce the use of Principal Component Analysis (PCA) for dimensionality reduction. When successfully implemented, the proposed system should be able to accurately classify images.

The Convolutional Neural Network (ConvNet) has recently achieved great success in many computer vision tasks. ConvNet was partially inspired by neuroscience and thus shares many of the brain’s properties. Training a ConvNet can be achieved by back-propagating the classification error, which requires a reasonable amount of training data based on the size of the network.

Image classification can be defined as the task of categorizing images into one of several predefined classes, is a fundamental problem in computer vision. Image classification forms the basis for other computer vision tasks such as localization, detection and segmentation. Image classification is an important task in the field of machine learning and image processing, which is widely used in many fields, such as computer vision, network image retrieval and military automation target identification.

ConvNets, as standard feature extractors, have been continuously used to improve computer vision in terms of accuracy. This implies expulsion of the traditional hand-crafted feature extraction techniques in computer vision problems. The features learned from ConvNets are generated using a general-purpose learning procedure. Combining both hand-crafted features and machine learned feature is increasingly becoming a hot spot.

The common architecture of ConvNets contains many layers to recurrently extract suitable image features and feed them to the softmax function (also known as multinomial logistic regression) for classification and replaced softmax with Biometric Pattern Recognition (BPR) and Support Vector Machine (SVM) respectively in order to overcome the limitation of softmax classifier which, often displays a low prediction performance.

At every stage of unsupervised learning K Nearest Neighbor (KNN) can perform better than the SVM. Principal Component Analysis (PCA) can also be used to reduce the dimension of the convoluted image. This work is aimed at proposing an improved Convolutional Neural Network (ConvNet) with reduced complexity and improves precision that can be easily trained and can adapt to different data and tasks for image classification.

To achieve this, KNN is going to be adopted as the classifier while PCA for image dimension reduction will is adopted at the fully connected layer before input into the KNN for classification as this is to reduce the complexity.

Principal Component Analysis (PCA) is one of the statistical techniques frequently used in signal processing, data dimension reduction or data decorrelation. PCA is often used in signal and image processing as it offers a powerful means for data analysis and pattern recognition which are used as a technique for data compression, dimension reduction or decorrelation. PCA represent data in a form that increases the mutual independence of influential components by means of Eigen-analysis.  

KNN is a simple algorithm that can store all available cases and classifies new cases based on a similarity measure. K-Nearest Neighbor (KNN) algorithm is one of the distinctive methods used in image classification. Nearest Neighbor classification of objects is based on their similarity to the training sets and the statistics defined. KNN’s basic idea is that if the majority of the k nearest samples of an image in the feature space belong to a certain category, the image also belongs to this category. KNN consists of two main procedures: similarity computing and k nearest samples searching. Since KNN requires no learning and training phases  and avoids overfitting of parameters, it has a good accuracy in dealing with classification tasks with more samples and less classes. The k nearest neighbor (KNN) classifier is based on the Euclidean distance between a test sample and the specified training samples.

When compared, the performance of unsupervised feature learning and transfer learning against simple patch initialization and random weight initialization within the same setup. They showed that pre-training helps to train CNNs from few samples and that the correct choice of the initialization scheme can push the network’s performance by up to 41% compared to random initialization. Their results show that pre-training systematically improves generalization capabilities when handling datasets with few samples. They concluded that the choice of a pre-training method depend highly on the dataset used. They used the traditional filter selection and softmax as their classifier.

On being evaluated and compared the performance of the support vector machine (SVM) and KNN classifiers is measured and the performances of the classifiers by using the confusion matrix technique. It was found that the KNN classifier was better than the SVM classifier for the discrimination of pulmonary acoustic signals.

A new class was derived, of fast algorithms for convolutional neural networks using Winograd's minimal filtering algorithms. The algorithms were derived for network layers with 3x3 as filter size for image recognition tasks. The algorithms reduced arithmetic complexity up to 4 times compared with direct convolution, while using small block sizes with limited transform overhead and high computational intensity. Work was basically concentrated on the convolution layer and did not consider other layers of the ConvNet.

The performance of different classifiers on the CIFAR-10 dataset, were studied and an ensemble of classifiers was build to reach a better performance. It was show that CIFAR-10, KNN and Convolutional Neural Network (CNN), on some classes, are mutually exclusive, and as such produced higher accuracy when combined. The concept of Principal Component Analysis (PCA) to reduce overfitting in KNN was applied, and then combined it with a CNN to increase its accuracy. The work combined the KNN with CNN for feature extraction which is different.

On investigated, a series of data augmentation techniques to progressively improve the prediction invariance of image scaling and rotation was done. SVM classifier as an alternative to softmax was used to enhance generalization ability. The recognition rate was up to 92.74% on the patch level with data augmentation and classifier boosting. The results showed that, the combined CNN-SVM model beats models of traditional features with SVM as well as the original CNN with softmax.

To deal with the problem associated with softmax classifier, proposed a new technique of combining Biometric Pattern Recognition (BPR) with ConvNets for image classification. BPR performs class recognition by a union of geometrical cover sets in a high-dimensional feature space and therefore can overcome some disadvantages of traditional pattern recognition. They evaluated the method using three image datasets: MNIST, AR, and CIFAR10. We are applying their concept but using KNN instead of the BPR.

Architecture was presented which combines a Convolutional Neural Network (CNN) and a linear SVM for image classification. They employed the use of a simple 2-Convolutional Layer with max-pooling. This was tested, architecture using Fashion-MNIST datasets and found that the CNN-softmax outperformed CNN-SVM. Hence, confess that there was no enough preprocessing of the data in the study and need to improve on the model to achieve more accurate results,

It was proposed that a Presentation Attack Detection (PAD) method called Spoof Detection for near-infrared (NIR) camera-based finger-vein recognition system using Convolutional Neural Network (CNN) to enhance the detection ability of previous handcrafted methods. This led to derive a suitable feature extractor for the PAD using ConvNet. This processed the extracted image features in order to enhance the presentation attack finger-vein image detection ability of the CNN method using Principal Component Analysis Method (PCA) for dimensionality reduction of feature space and Support Vector Machine (SVM) for classification. Through extensive experimental results, it was endorsed that this proposed method is suitable for presentation of attack finger-vein image detection and it can deliver superior detection results when compared  with other ConvNets methods.

The use of fully convolutional architectures in the notable object detection systems such as Fast/Faster RCNN to replace the fully connected layer of ConvNets was presented. A general formula was derived, specifically to accurately design the input size of the various fully convolutional networks in which the convolutional layer and pooling layer are concatenated with their strides and have proposed an efficient architecture of skip connection to accelerate the training process. This compared the model with Fast RCNN and the accuracy increased by about 2%. The method was tested using a very small data set. Again, using CNN as a classifier might not be feasible because fully connected layer is able to generalize the feature extracted into the output space and also the output need to be scaler.

During the work, a k-Tree method to learn different optimal k values for different test and new samples, by involving a training stage in the kNN classification was proposed. In the training stage, k-Tree method first learns optimal k values for all training samples by a new sparse reconstruction model, and then construct a decision tree using training samples and the learned optimal k values. In the test stage, the k-Tree obtained as output the optimal k value for each tested sample, before the kNN classification was carried out using the learned optimal k value and all training samples. The model had similar running cost but higher classification accuracy, compared with traditional kNN methods but less running cost. It was also realized that similar classification accuracy, compared with the new kNN methods, which assign different k values to different test samples is possible.

Confusion Matrix (explained below)

Positive(P): Observation is positive

Negative (N): Observation not positive

True Positive (TP): Observation is positive and is predicted positive

True Negative (TN): Observation is negative and is predicted negative

False Positive (FP): observation is negative but predicted positive

False Negative (FN): Observation is positive but predicted negative

We  tend to design an improved Convolutional Neural Networks (ConvNets) with improved precision and accuracy. We employ the use of Principal Component Analysis (PCA) to reduce the dimension of the image and K Nearest Neighbor (KNN) for classification. When successfully implemented, the proposed system should be able to accurately classify images based on a given training set and test set. It will be evaluated in terms of accuracy.

[allmathtricks]

Arithmetic Progression Formulas for find nth term, sum to first nth term...

[entranceidelhi]

RD Sharma Solutions Class 11 Math PDFs Free Download with Entrancei

https://entranceidelhi.livejournal.com/988.htmlRD Sharma Class 11 Solutions depend on the refreshed prospectus of Central Board of Secondary instruction (CBSE) as indicated by the CCE (Continuous and Comprehensive Evaluation) rules. The course readings are encircled for class 11 CBSE understudies. Here at Entrancei.com you will locate the total RD Sharma Solutions Class 11 for all inquiries in the manual with the goal that understudies can without much of a stretch comprehend the ideas.

Important Features of RD Sharma Maths Solutions:

1. These math solutions are created by our math experts to provide complete and accurate solutions for each question, along with solved examples of RD Sharma textbook.

2. These solutions are comprehensive and are explained step by step for better learning and understanding.

3. These solutions are very useful for preparing for exams at school and graduate level such as NTSE, KVPY, NSO, IMO, CAT, GRE, IIT JEE and more.

4. These solutions help to master the basic mathematical concepts from the start.

5. Brief summary composed of formulas and concepts.

RD Sharma class 11 solutions for all mathematical chapters are given mentioned below. There are many important topics in class 11, which are discussed in detail here. Students can get complete solutions to all RD Sharma questions to prepare for their exam.

RD Sharma Solution Class 11 Maths Chapter’s Name

Sets

Relations

Functions

Measurement of Angles

Trigonometric Functions

Graphs of Trigonometric Functions

Trigonometric Ratios of Compound Angles

Transformation Formulae

Trigonometric Ratios of Multiple and Sub Multiple Angles

Sine and Cosine Formulae and Their Applications

Trigonometric Equations

Mathematical Induction

Complex Numbers

Quadratic Equations

Linear Equations

Permutations

Combinations

Binomial Theorem

Arithmetic Progressions

Geometric Progressions

Some Special Series

Brief Review of Cartesian System of Rectangular Coordinates

The Straight Lines

The Circle

Parabola

Ellipse

Hyperbola

3D Coordinate Geometry

Limits

Derivatives

Mathematical Reasoning

Statics Probability

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It can be your favorite place to get the latest updates and the latest authenticated news in the field of education. Whether it's JEE Mains, the CBSE board review, or any other state board review, our educational blog is a well-established online landscape for students of all ages to read about all subjects in education. Stay up-to-date with news and trends and check back regularly for the latest information on education and all kinds of tests. Start exploring now!

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NCERT Solutions for class 10 maths

Class 10th maths is crucial of all the subjects, as it helps in building the foundation of the future technical courses. The ncert solutions for class 10 maths provided comprises of solutions to all the exercises given in CBSE textbook. The expert team at entrencei have keenly evaluated and reviewed the complete set of material. And to help you we have uploaded Maths formula in one page for effective revision .We solely believe in providing the best of ncert solutions for class 10 maths in order to ease the process of learning. In case if you face any issue regarding the material provided, then you can directly reach to our executives.

 The level of education provided by NCERT helps in creating a strong base for the one looking to higher technical studies. the continuous effort of the team at entrencei have led to provide you with an extensive list of chapters solution to ncert solutions for class 10 maths of which chapters are mentioned below:

 Chapter 1 – Real Numbers

This topic of ncert solutions for class 10 maths comprises of extension provide to 9th class. One would be made aware of the intrinsic details of Euclid’s division algorithm, rational numbers. The ncert solutions for class 10 maths provide help in understanding divisibility of integers.

 Chapter 2 – Polynomials

This part of ncert solutions for class 10 maths comprises of four exercises.  All the exercise mentioned deal around determining zeroes of polynomials, quadratic polynomials.

 Chapter 3 – Pair Of Linear Equation In Two Variables

The introduction to this chapter mentioned in ncert solutions for class 10 maths comprises of laying concepts of linear equations in two variables. In this chapter detailed study could be made of the graphical method and algebraic method of solving linear equations. Elimination method, substitution method, cross-multiplication method are explained in exercises format.

 Chapter 4 – Quadratic Equation

This ncert solutions for class 10 maths comprises of methods to find roots of the quadratic equation. The exercises mentioned would comprise of questions related to our day to day life problems. One will study regarding completing the square and factorization method to determine roots of quadratic equations. Nature of roots are the main topics to be studied in this ncert solutions for class 10 maths.

 Chapter 5 – Arithmetic Progressions

This topic of ncert solutions for class 10 maths has minor complex problems related summation of consecutive terms. This topic helps in finding solutions to real-life problems.

 Chapter 6 – Triangles

This chapter consists of questions based upon properties of triangles which are very extensively explained in ncert solutions for class 10 maths provided by us. The main 9 theorems mentioned in it are of main importance with respect to exams.

 Chapter 7 – Coordinate Geometry

This chapter has been holding a very crucial place, as it helps in finding the distance between two coordinates provided. The ncert solutions for class 10 maths to this chapter have been made very entreating to understand for students.

 Chapter 8 – Introduction to Trigonometry

This chapter comprises of determining trigonometric ratios of acute angles of triangles. The ncert solutions for class 10 maths provide for ratios of complementary angles are main topics to be focused upon.

 Chapter 9 – some applications of Trigonometry

This chapter will bring you some new sides of solving mathematics as provided by our team in ncert solutions for class 10 maths.

 Chapter 10 – Circles

Here you will be brought some untouched theorems and formula of the circle.

 Chapter 11 – Construction

Here you will be using ruler and compass to draw some geometric figures. Carving out bisector of angle and triangles construction has been very extensively mentioned in ncert solutions for class 10 maths.

 Chapter 12 - Areas related to Circles

You must be well acquainted with finding areas of different geometric plane figures. The reference of ncert solutions for class 10 maths would the chapter very easy.

 Chapter 13 – Surface Areas and Volumes

Well, this chapter is the continuation of 9th standard. One will be made acquainted with volumes and areas of cubes, cuboid, and cylinders.

 Chapter 14 – Statistics

Here you will be calculating mean, median and mode to grouped data. The problems related to cumulative frequency will also be worked upon.

Chapter 15 – Probability

Students will be made acquainted with the values of probability lying between zero and one.

 Why Entrancei

The expert team at Entrancei has created some awesome content as presented in the form of ncert solutions for class 10 maths. We believe in providing a complete solution to students.

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Class 10 Maths CBSE Board Exam is harder than class 9 maths as new concepts and topics are introduced here. 2 to 3 hours of self-study will be sufficient for your board exam preparations.

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Sequences and Series

Sequences and Series

Sequences: A sequence is a set of terms in a definite order with a rule for obtaining the terms. e.g. 1, 1/2, 1/3 ,……., 1/n,…….. is a sequence. Arithmetic Progression (AP): AP is a sequence whose terms increase or decrease by a fixed number. This fixed number is called the common difference. If a is the first term & d the common difference, then AP can be written as a, a + d,…

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Sequences and Series

Sequences and Series

Sequences: A sequence is a set of terms in a definite order with a rule for obtaining the terms. e.g. 1, 1/2, 1/3 ,……., 1/n,…….. is a sequence. Arithmetic Progression (AP): AP is a sequence whose terms increase or decrease by a fixed number. This fixed number is called the common difference. If a is the first term & d the common difference, then AP can be written as a, a + d,…

[learncbse-science]

Sequences and Series

Sequences and Series

Sequences: A sequence is a set of terms in a definite order with a rule for obtaining the terms. e.g. 1, 1/2, 1/3 ,……., 1/n,…….. is a sequence. Arithmetic Progression (AP): AP is a sequence whose terms increase or decrease by a fixed number. This fixed number is called the common difference. If a is the first term & d the common difference, then AP can be written as a, a + d,…

[learncbse6]

Sequences and Series

Sequences and Series

Sequences: A sequence is a set of terms in a definite order with a rule for obtaining the terms. e.g. 1, 1/2, 1/3 ,……., 1/n,…….. is a sequence. Arithmetic Progression (AP): AP is a sequence whose terms increase or decrease by a fixed number. This fixed number is called the common difference. If a is the first term & d the common difference, then AP can be written as a, a + d,…