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      "body": "![robot-library-cyborg-2.jpg](https://steemitimages.com/DQmSyKvBTdyUSEm6qsMjMa5om7iJMRCUFP2ctmiyYYtSf6i/robot-library-cyborg-2.jpg)\n# Machine Learning Reference Material Guide\n\n## Math Theory\n\n### Linear Argebra:\nIn ML, Linear Algebra comes up everywhere. Topics such as Principal Component Analysis (PCA), Singular Value Decomposition (SVD), Eigendecomposition of a matrix, LU Decomposition, QR Decomposition/Factorization, Symmetric Matrices, Orthogonalization & Orthonormalization, Matrix Operations, Projections, Eigenvalues & Eigenvectors, Vector Spaces and Norms are needed for understanding the optimization methods used for machine learning.\n- Deep Learning Book, Chapter 2: Linear Algebra. A quick review of the linear algebra concepts relevant to machine learning. https://goo.gl/O5vgpm\n- A First Course in Linear Model Theory by Nalini Ravishanker and Dipak Dey. Textbook introducing linear algebra in a statistical context. https://goo.gl/2A4Wi5 \n\n### Probability Theory and Statistics:\nBecause Machine Learning and Statistics aren’t very different fields.  Some of the fundamental Statistical and Probability Theory needed for ML are Combinatorics, Probability Rules & Axioms, Bayes’ Theorem, Random Variables, Variance and Expectation, Conditional and Joint Distributions, Standard Distributions (Bernoulli, Binomial, Multinomial, Uniform and Gaussian), Moment Generating Functions, Maximum Likelihood Estimation (MLE), Prior and Posterior, Maximum a Posteriori Estimation (MAP) and Sampling Methods.\n- All of Statistics: A Concise Course in Statistical Inference, by Larry Wasserman. Introductory text on statistics: https://goo.gl/lSSXYU\n\n### Calculus:\nSome of the necessary topics include Differential and Integral Calculus, Partial Derivatives, Vector-Values Functions, Directional Gradient, Hessian, Jacobian, Laplacian and Lagragian Distribution.\n- Calculus: A Complete Introduction by Hugh Neill: https://goo.gl/WsMJYG\n\n### Algorithms and Complex Optimizations:\nThis is important for understanding the computational efficiency and scalability of our Machine Learning Algorithm and for exploiting sparsity in our datasets. Knowledge of data structures (Binary Trees, Hashing, Heap, Stack etc), Dynamic Programming, Randomized & Sublinear Algorithm, Graphs, Gradient/Stochastic Descents and Primal-Dual methods are needed.\n- Data Structures and Algorithms in Java. By Robert Lafore: https://goo.gl/CJXDq2 Although it has Java in the title, the content of this book applies to any other language.\n\n## Machine Learning:\n- Deep Learning (Adaptive Computation and Machine Learning series) by Ian Goodfellow: https://goo.gl/O5vgpm\n- Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems: https://goo.gl/mDxPaU",
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      "body": "![](https://steemitimages.com/DQmV4XprGdSSdpjrNXsyxgd8tiEdpbR4z7aVHoTM7BtzEe9/image.png)\n## What is Social Selling?\n\nSocial Selling is the process of developing relationships as part of the sales process. Today, this often takes place via social networks such as LinkedIn, Twitter, and Facebook, but can take place either online or offline.\n\n## The Idea\n\nI’m part of the Engineering Team in charge of developing social selling solutions at Hootsuite. This year, we developed Amplify for Selling, a mobile app designed to help sales reps generate leads and fostering relationships that drive revenue. So, ever since we had a first working prototype (way before the official launch) I started using it everyday, so I could prove to myself, and my team, that the vision that we set for this solution was real!\n\n## The Process\n\nI could call myself a lot of things, but “Sales Rep.” is certainly not one of them. If I wanted to prove that our app and social selling works, then I had to sell something. That’s when the idea came; why not sell or promote my image, myself? Selling doesn’t have to be limited to material things, right?\n\nSo that’s what I did, I set up Amplify for Selling in a way you set it up when selling any product:\n\n1. Connected my Twitter account.\n2. Set up Keywords so every time there were signs of my contacts posting related messages (social signals), I would get a push notification on my phone.\n\n![Amplify for Selling. Contact View](https://steemitimages.com/DQmbAHTi6R293PfTuXGi8byz4ryPxR8PJcHDKsFoS38J8o9/image.png)\n\nThe difference was, that instead of entering keywords related to a product, I setup keywords related to my professional interests: engineering, programming, leadership, machine learning, open source, etc.\n\nSoon enough, I started getting push notifications when a contact posted things related to my professional interests. This allowed me to engage with them on social media (like, reply, quote), which in return, increased my number of followers, expanded my professional network and helped me nurturing my existing connections.\n\nAmplify for Selling also provides you with content, curated by your organization, so you can share it out to your social networks. I didn’t have to set anything special for that. I only shared content that I thought my audience (mostly Tech) would be interested in. This expanded the reach of my own messages within the networks that I was targeting.\n\n![](https://steemitimages.com/DQmRYQr1HtfQHKAs3GXeLz1ccuxEme5VpJZhqe6rmvdwLQZ/image.png)\n\n## The Results\n\nI was completely blown away by the increase of the number of followers in such a short period of time. Below if a graph that shows how, the moment I started using the app for social selling (February 2017), I almost instantly doubled my followers, and then in a matter of weeks, I tripled, and quadrupled the original number!\n\nAll of the sudden, I was able to engage in online conversations with my followers (via Twitter), created new connections, and developed relationships with people in my area of professional expertise.\n\n![](https://steemitimages.com/DQmZhmGjWoFnMFUdB4Hcmu75zjPrQEdEo4Hq2jrq7iMdGPh/image.png)\n\n## Conclusion\n\nImagine having that amount of boost in online reach, and influence, if you were selling an actual product! Social Selling is a necessary and effective response to a changing selling environment. Some remain skeptical, however, the numbers obtained by this experiment show that there is an opportunity that should not be missed, and that the original vision that my team set when we started building the app, was real.",
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